PRC Report Series 2008- 1 FERTILITY AND CONTRACEPTIVE ...

Executive SummaryFertility in Malappuram, the largest district in India in terms of population size, hasbeen declining but it still has the highest birth rate in the state. Identification of highfertility areas within the district and efforts for effective planning, implementation andmonitoring aspects is a serious problem today due to the lack of data at the micro levelespecially below the district level. So, on the basis of data available at the panchayatlevel, using Reverse survival technique, which is found to be the most adequate tool toestimate fertility as it requires minimum information compared to other estimates, birthrate at the panchayat level is estimated. The estimated birth rates are further classifiedusing the statistical technique of cluster analysis. Generation of thematic maps based onestimated fertility rates at the Panchayat level using Geographic Information Systemsoftware is also embarked upon in the present study. Using Reproductive and ChildHealth Survey 2004 Round II data, Multiple Classification Analysis (MCA) wasemployed to understand the probable factors that explain high fertility in Malappuram,and Logistic Regression Analysis was employed to find out the determinants ofcontraceptive use.Birth rate in Malappuram district for the period 1997-2001 is 23.3 births per 1000population. Among the 100 panchayats as of 2001, the panchayat with maximum birthrate is Pookkottur panchayat of Malappuram block in Ernad Taluk with a birth rate of27.8 and the least in Perumpadappu panchayat (18.4) of the block of the same name inPonnani taluk. Cluster analysis showed that only one panchayat stood out from the restand forms an outlier. This outlier was Pookkottur panchayat of Malappuram block inErnad Taluk with a birth rate of 27.8. Panchayats with birth rates above the districtaverage were mainly concentrated in the Ernad and Tirurangadi taluks. Nilambur,Perinthalmanna and Tirur taluks also had a few panchayats with higher birth rates.Ponnani taluk was an exception from the lot in the sense that all the panchayats hadvery low birth rate ranging from 18.4 to 20.6. Tirur taluk was also better placed in thisregard as 14 panchayats have birth rate below the district average.Thematic maps generated on the basis of the estimated fertility rates using GIS softwareenabled to explore the possible association of socio economic, and demographic factorson fertility. The inverse relationship between literacy and fertility could be proved to acertain extent in Malappuram district. Birth rate was generally high in panchayats withlow work participation rate and vice verse though there were many exceptions to thisobservation. A positive association was discernible between proportion of agriculturallabourers and fertility. In some of the panchayats with higher proportion of agriculturalworkers, birth rate was also high as in the case of Vazhikadavu, Thazhekkode, Pozhur,Pandikad etc. The panchayats with low proportion of cultivators and low birth ratewere mostly in Ponnani Taluk, and some panchayats in Nilambur Taluk.4

List of TablesSl. No. Tables Page No.1.1 Demographic profile of Malappuram District 121.2 Vital Rates- Malappuram district 122.1 Block Wise Panchayat List, Malappuram 2001 182.2 Panchayat wise population Malappuram, 2001 202.3 Municipality Population, Malappuram, 2001 242.4 Birth Rate of Panchayats in Malappuram district,1996-2001282.5 Classification of Panchayats by birth rate intodifferent clustersWomen classified according to the Children ever3.1born and their background characteristics3.2 Results of Multiple classification analysis 494.1Percentage distribution of women classified by theirbackground characteristics564.2 Contraceptive Prevalence Rate 584.3 Type of Contraceptive methods used 584.4 Unmet Need for Family Planning 594.5Percentage distribution of women currently usingcontraceptives classified by their background60characteristics4.6 Variables included in the regression analysis 634.7 Results of Logistic regression analysis showing thedeterminants of contraceptive use in Malappuram3145646

List of MapsSl. No. Figures Page No.1 Malappuram District Map 102Age Structure of the population of Malappuramdistrict 1971-2001142.1 Panchayat Wise Population of MalappuramDistrict, 2001254Panchayat wise Birth Rate, Malappuram (1996-2001)3456Panchayat Wise Birth Rate and Sex Ratio ofMalappuram District, 2001Panchayat Wise Birth Rate and Literacy ofMalappuram District, 200137387Panchayat Wise Birth Rate and Distribution of TotalWorkers of Malappuram District, 2001398Panchayat Wise Birth Rate and Distribution ofAgricultural Workers of Malappuram District, 2001409Panchayat Wise Birth Rate and Distribution ofCultivators of Malappuram District, 2001417

Chapter IIntroduction1.1 About the DistrictMalappuram is literally known as a land a tops hill. It is situated 50 kilometerssouth-east of Kozhikode district, bounded by the Nilgiri hills in the east, theArabian Sea in the west and Thrissur and Palakkad district in the south. BeforeIndia's Independence in 1947, Malappuram was part of Malabar District in theMadras Presidency of British India. The area covered by the present district wasadministered as part of Kozhikode, Ernad, Valluvanad and Ponnani taluks.Malabar District remained part of Madras state immediately after IndianIndependence. Later, merging the distant and backward areas of the erstwhileKozhikode, Perinthalmanna and Ponnani taluks of Palakkad, Malappuramdistrict was formed on the 16 th June 1969. The location of Malappuram district is75° to 77° east longitude and 10° to 12° north latitude, in the geographical map.Three great rivers flowing through it - the Chaliyar, the Kadalundi and theBharathappuzha, enrich it. Like most of the other districts of the state,Malappuram too consists of three natural divisions; lowland, midland andhighland. The low land stretches along the sea coast, the midland in the centreand the highland region towards the east and north eastern parts. Thetopography of the district is highly undulating; starting from the hill topscovered with thick forests on the east along the Nilgiris, it gradually slopes downto the valleys and the small hills, before finally ending on the sandy flat ofluxuriant coconut groves in the west. The district has a geographical area of 3550Sq. Kms of which 28.5 percent is covered by forests.The district has more or less the same climatic conditions prevalent elsewhere thestate, viz. dry season from December to February, hot season from March to8

May, the Southwest Monsoon from June to September and the North EastMonsoon from October to November. The South West Monsoon is usually veryheavy and nearly 75% of the annual rains is received during this season. Theclimate is generally hot and humid; the range of temperature varying between30° C and 20° C. The average annual rainfall is 2900 mm.Muslims constitute the majority of the population, and next comes the Hinduand the Christian communities respectively. The Muslims of Malappuramdistrict are known as Mappilas. A great majority of them are traditional Sunnisfollowing the Shafi School of thought and the second majority is the followers of"Salafi" thoughts. They are known as Kerala Nadvathul Mujahideen,who causedan accelerated growth in social development and education among Muslims. Allof the social reforms in and around Malappuram District is due to the historicalrenaissance activities lead by Kerala Nadvathul mujahidheen and its alliedorganizations. Malappuram is the birth place of number of Muslim scholars andorators.Headquarters of the administration is at Malappuram, with Collectorate andmain offices in the civil station. The district has two revenue divisions withheadquarters at Perinthalmanna and Tirur. Presently there are 6 taluks,namely Ernad (headquarters at Manjeri), Perinthalmanna, Tirur, Ponnani,Nilambur and Tirurangadi (headquarters at Parappanangadi). The taluks ofNilambur and Tirurangadi and the revenue division of Tirur, were formedrecently. These are further divided into 135 Villages, 14 blocks, 5Municipalities and 100 panchayats. Of the 135 villages, 19 are in Nilamburtaluk, 33 in Ernad, 24 in Perinthalmanna, 30 in Tirur, 11 in Ponnani and 18 inTirurangadi taluk.9

Figure1. Malappuram District Map10

1.2 Demographic Profile of the DistrictThe population of Malappuram has been rising rapidly in size since its formation(Table 1.1). The 1971 census placed the population at 1856357. It has almostdoubled in the three decades that followed as the census 2001 figures put thepopulation at 3625471. Looking at the Taluk wise population, Tirur is the mostpopulated taluk with 8.3 lakhs followed by Ernad taluk with 7.8 lakhs. The leastpopulated one is Ponnani (3.5 lakhs). Out of the total population of the district,1754576 are males and 1870895 are females, forming a ratio of 1066 females forevery 1000 males, the state ratio being 1058 females for 1000 males. Among the 6taluks, the sex ratio is highest in Ponnani (1104) and least in Ernad (1024). Thesex ratio of the 0-6 population among the taluks is favourable to female childrenonly in Perinthalmanna taluk (1114).With regard to the growth rate of population, up to 1961, the decadal growthrates of Malappuram district were far below the state average (Table 1.1).However, the rates for both decades 1961-71 and 1971-81 are higher than thestate average (Malappuram 1961-71: 33.80 and 1971-81: 29.43 as against Kerala1961-71: 26.29 and 1971-81: 19.24). During 1981-91, Malappuram recorded agrowth rate of 28.87 percent. This district has been the focus of attention eversince the 2001 Census showed that the district recorded the biggest decline in thegrowth rate of population in Kerala. A steep fall by 11.65 percentage points from1981-91 puts the decadal growth rate at 17.22 percent during 1991-2001. Thoughthis rate is pretty high compared to other districts, it signifies a dramatic drop inthe birth rate in Malappuram.11

Table 1.1: Demographic profile of Malappuram DistrictDemographic 1971 1981 1991 2001indicatorsTotal Population 1856357 2402701 3096330 3625471Population (percent to total)0-14 years + 29.8 41.6 39.1 34.115-59 years + 62.5 52.0 54.3 58.660+ years + 5.8 6.4 6.6 7.3Decadal variation 33.8029.4328.8717.22(1961-71)(1971-81)(1981-91)(1991-2001)Density 523 677 872 1021Sex Ratio 1041 1052 1053 1066Percent urban 6.73 7.40 9.12 9.82Literacy rate, total 56.77 70.3 87.9 91.60Male 66.01 77.14 92.1 94.76Female 48.0 63.88 84.1 88.68Dependency ratioTotal95.7 92.3 84.0 70.6Young70.8 65.8 59.8 48.3Aged10.8 12.2 12.0 12.4+ Percentage to total populationTable 1.2: Vital Rates- Malappuram district1991 2001Crude Birth rate 36.55 22.4*Total Fertility rate 4.21 2.4*Infant Mortality Rate 35*** Estimated figures: Guilmoto and Rajan, 200212

**District Profile RGI 1998, Census of India 1991The density of population is 1021 persons per sq. kms., which is much higherthan the state average (819 persons per sq. kms). Marked increase in density ofpopulation has occurred since 1961 (391). It rose to 523 in 1971, 677 in 1981 and872 in 1991. Increasing educational status of the people in Malappuram similarto the other districts is evident from Table 1.1. The total literacy rate inMalappuram district increased from 56.8 percent during 1971 to 87.9 percentduring 1991. All through the four decades the rate has been more among themales than the females. Literacy rate of the total population as per 2001 census isput at 89.61 percent, males: 94.8 percent and females: 88.7 percent. Ernad taluk isthe most literate (94.1 percent) and Nilambur the least (81.4 percent).Subsequently, Malappuram District was declared 100 percent literate along withother districts of the state; made possible by in intensive statewide literacy drive.The percentage of urban population in the district is only one-fourth that of thecorresponding proportion for the state (about 26 percent). The urban populationincreased from 6.73 to 9.12 percent during the 1971-91 period. The 2001 censusputs this percentage at only 9.82 percent.1.2.1 Age Sex Distribution of Population- Malappuram DistrictThe Age Sex distribution of population as depicted by the Age-Sex Pyramidgives an idea about the changes in the age structure of the population of thedistrict. The gradual narrowing of the base and the broadening of the apex (70+years) shows the ageing process. The bulge in the population aged 15-59 years orthe economically active population compared to the dependent population or the0-14 year and 60+ year age groups sketches the dependency burden of the13

population. Figure 2 portrays the changing age structure of the population ofMalappuram district from 1971 to 2001. It is quite evident that the proportion ofchildren has been almost unchanging during 1971 to 1991. But the decline infertility during the recent years is visible in the age sex pyramid of the year 2001.The dependency burden still continues to be high though it has declined over thepast 40 years (Table 1). The total dependency ratio, expressed as the ratio ofpopulation 0-14 and 60+ years to population 15-59 years, has declined from 95.7to 70.6 percent only during 1971-2001. When the Young dependency burden(ratio of population aged 0-14 years to those aged 15-59 years) declined from 70.8to 48.3 percent during 1971-2001, the aged dependency burden (ratio ofpopulation aged 60+ years to those aged 15-59 years) has increased onlymarginally from 10.8 to 12.4 percent during the same period. Since fertility hasstarted declining at a relatively faster pace only recently the young dependencyratio will reduce further only in the years to come. The sex ratio in Malappuramwhich is favourable to females as in the state is quite evident from the shape ofthe pyramid.Figure 2: Age Structure of the population of Malappuram district 1971-200170+60-6450-5440-4430-3420-2410-14197170+60-6450-5440-4430-3420-2410-1419810-4MalesFemalesMales0-4Females14

70+60-6450-5440-4430-3420-2410-14199170+60-6450-5440-4430-3420-2410-1420010-4MalesFemalesMales0-4FemalesMalappuram district is projected to be the most backward district in Kerala. Thisdistrict also has a place in the list of backward districts in India as classified bythe Union Ministry of Health and Family Welfare in India. Based on thecomposite index developed on the basis of socio-economic and demographicindicators by Ram and Shekhar (2006), this district is still placed at a very lowposition compared to the other districts of Kerala. The rank of this district withregard to the composite index is 180 out of a total of 591 districts when most ofthe other districts of the state are well placed. The brief profile of the districtgiven hitherto highlights how the district is placed with regard to thedemographic achievements. It specifically projects the high fertility in thedistrict. This study is planned to bring out the possible aspects that couldexplain the high fertility in the district. Lack of data at the grass root level oftenhampers micro level analysis. Hence estimation of fertility at the panchayat levelis embarked upon as the preliminary objective.1.3 ObjectivesThe main objectives of the present study on Malappuram district are:1 Estimation of fertility at the panchayat level15

Chapter IIEstimation of Fertility at Panchayat level2.1 IntroductionAvailability of data related to key social, economic and demographic indicatorsfor micro level planning is an important factor in planning, administrative anddevelopment process. The National and Small Sample surveys provide relevantinformation at the National, State and District level on population, growth rate,vital statistics etc. However scarcity of data published below the district leveloften hampers governmental efforts aimed at planning and monitoring of areaspecific development. Hence, the requirement of appropriate database at themicro-level, particularly in view of decentralization of administrative authorityand planning process makes it imperative to search for alternative data sources.Some of these requirements can be met through the method of IndirectEstimation of rates from available information. This section deals with one suchobjective.The Sample Registration System is the most important source of data with regardto the estimates on fertility and mortality rates. It provides data on CBR, CDRand IMR on the national basis and also state wise ever since 1971. Looking at theavailability of data on fertility below the state level, in Kerala, except of thedistrict wise estimates of fertility provided by Rajan and Zachariah (1998), Rajan(2002) and Bhat (1996), there seems to be no other important source. Some areaspecific studies also provide fertility estimates for the districts where the studieswere conducted (World Bank, 1980). Fertility data at the Panchayat level isvirtually non-existent and hence using indirect techniques an attempt is madehere to estimate fertility at the Panchayat level.17

As Malappuram district is found to be lagging behind in demographicachievements, especially fertility rate when compared to the other counterparts,particular focus has to be given to distinctive areas in the district that lags behindin development. So using indirect techniques the fertility rate at Panchayat levelis estimated here.2.2 Panchayat Level StatisticsMalappuram district has two Revenue Divisions with headquarters atPerinthalmanna and Tirur. There are 6 Taluks, namely Eranad, Perinthalmanna,Tirur, Ponnani, Nilambur and Triurangadi. The District has been divided into 14Blocks and 100 Panchayats, for the sake of development programs. The detailedblock wise Panchayat list for which fertility is estimated using indirecttechniques is given in Table 2.1.Table 2.1: Block Wise Panchayat List, Malappuram 2001Name of Block No. of Name of PanchayatsPanchayatsAreacode 7 Keezhuparamba, Areacode, Cheacode,Kuzhimanna, Kavanur, Pulpatta, UrngattiriKondotty 8 Chelembra, Cherukavu, Kondotty, Pallikal,Pulikkal, Nediyiruppu, Vazhakkad, VazhayoorKuttippuram 6 Athavanad, Edayur, Irimbiliyam, Valanchery,Kuttippuram, MarakkaraMalappuram 6 Anakkayam, Kottakkal, Morayur, Pookkottur,Ponmala, OorakamMankada 9 Angadipuram, Kodur, Koottilangadi, Kuruva,Mankada, Makkaraparamba, Moorkanad,Pulamanthole, PuzhakkattiriName of Block No. of Name of PanchayatsPanchayatsNilambur 11 Amarambalam, Chaliyar, Chungathara,Edakkara, Moothedam, Karulai, Kalikavu,Nilambur, Vazhikadavu, Chokkad, PothukalluPerinthalmanna 7 Aliparamba, Edapatta, Elamkulam, Keezhattur,Melattur, Thazhekode, Vettathur18

Perumbadappu 5 Alancode, Maranchery, Nannamukku,Perumpadappu, VeliyancodePonani 3 Edappal, Thavanur, VattamkulamTanur 9 Cheriyamundam, Kalpakanchery, Ozhur,Ponmundam, Tanur, Tanalur, Valavannur,Niramaruthur, Perumanna KlariTirur 6 Purathur, Thalakkad, Thirunavaya, Triprangode,Vettam, MangalamTirurangadi 7 Moonniyur, Nannambra, Parappanangadi,Tirrurangadi, Valikunnu, Tenhipalam,PeruvallurVengara 7 A.R.Nagar, Edaricode, Othukkungal, Parappur,Thennala, Vengara, KannamangalamWandoor 9 Edavanna, Karuvarakundu, Mambad,Pandikkad, Porur, Thuvvur, Thiruvaly,Thrikkalangode, WandoorPopulation of the Panchayats, sex ratio, literacy, work participation rate theproportion of workers to total population), the proportion of AgriculturalLabourers and Cultivators (proportion of Main and Marginal category ofagricultural labourers and cultivators to the total workers) in Malappuramdistrict is given in Table 2.2. Panchayats are arranged in ascending order ofPopulation size. Accordingly, Makkaraparamba panchayat of Mankada blockand Perinthalmanna Taluk is the least populated panchayat (1.6 lakh approx.)and Tanur panchayat of Tanur block and Tirur Taluk is the most populated one(6.3 lakhs). The sex ratio of the population is favourable to males in only onepanchayat which is Kavannur panchayat (996) of . The highest sex ratio is seen inTalakkad panchayat. However sex ratio of 0-6 population is favourable to malesin majority of the panchayats barring 7 panchayats and in one panchayat sexratio is perfectly balanced (1000). Its least in Kannamangalam (871) and highestin Makkaraparamba (1050).19

Table 2.2: Panchayat wise population Malappuram, 2001SlNoPanchayatNo. ofHouseholdsTotalPopnSexratioofPopnSexratio0-6PopnLiteracyWorkparticipationRateAgriculturalLabourersCultivatorsMale Female Males Female Male Female Male Female1 Makkaraparamba 2787 15934 1059 1050 81.5 77.8 41.8 6.8 11.6 30.6 7.8 9.02 Kizhuparamba 3418 18348 1039 953 81.0 76.8 46.0 6.5 14.8 19.9 7.1 1.83 Chaliyar 3816 19053 1056 927 74.6 69.1 51.3 16.0 22.8 32.1 10.6 3.64 Edappatta 3466 20321 1076 958 74.9 69.9 44.8 11.7 37.5 65.9 15.2 5.25 Karulai 3959 20758 1095 963 75.7 69.4 46.8 12.3 22.6 43.4 9.3 5.26 Moothedam 4289 22088 1062 953 75.3 70.7 47.7 13.6 39.4 55.2 15.6 5.17 Ponmundam 3566 23173 1113 992 76.5 70.9 37.8 2.6 9.6 10.6 5.6 5.88 Elamkulam 4254 23607 1096 939 79.6 77.2 42.9 10.1 27.3 38.0 11.4 7.39 Edarikode 3943 23722 1069 974 78.5 74.0 41.2 5.1 14.0 17.8 8.5 7.610 Melattur 4226 23823 1080 1004 77.2 72.2 43.8 9.1 31.5 43.5 11.5 2.711 Vettathur 4002 23955 1063 966 76.7 72.0 42.5 11.1 29.7 39.8 17.1 14.812 Thiruvali 4747 24275 1093 980 79.4 74.8 48.8 13.1 27.6 46.2 8.6 3.313 Edakkara 4924 24490 1059 979 79.5 75.8 48.0 9.9 27.1 28.1 9.1 3.814 Perumanna Clari 3825 24578 1096 963 77.1 72.4 34.6 2.0 12.9 7.9 7.7 5.515 Thennala 3922 25492 1075 908 76.7 72.0 32.5 1.7 8.9 4.4 5.6 4.816 Niramaruthur 3824 25547 1062 986 78.4 74.3 43.0 3.4 4.7 7.1 1.7 4.217 Porur 4510 25631 1066 927 75.7 71.4 45.3 10.2 29.3 50.2 9.8 3.018 Puzhakkattiri 4487 25676 1064 914 77.5 74.0 44.3 11.7 21.7 28.0 11.7 5.519 Kondotty 4145 25984 1027 941 78.9 74.0 43.2 3.5 13.3 16.0 3.3 3.020 Urakam 4198 26138 1046 994 77.8 72.4 36.9 4.5 9.5 11.9 9.5 5.521 Nannamukku 4981 26669 1139 994 79.7 74.9 43.3 9.4 11.2 25.9 10.6 11.622 Nediyiruppu 4335 26680 1035 978 79.1 73.9 42.9 6.9 17.1 28.0 7.7 6.423 Thuvvur 4625 26795 1065 942 75.0 71.0 45.0 9.3 22.9 35.3 10.5 4.624 Irimbiliyam 4610 27075 1099 976 79.4 76.1 42.8 6.9 10.7 23.4 6.9 2.425 Pothukal 5342 27118 1053 964 77.2 72.9 48.1 10.5 28.1 38.2 13.2 4.626 Thenhippalam 5114 27273 1052 985 82.2 77.4 44.8 7.8 12.6 6.1 3.2 0.727 Vazhayur 4987 27378 1016 927 83.7 79.5 49.6 5.7 13.3 15.9 3.2 3.628 Areekode 4662 27531 1002 954 78.7 73.2 43.3 5.8 21.6 21.1 6.5 2.720

SlNoPanchayatNo. ofHouseholdsTotalPopnSexratioofPopnSexratio0-6PopnLiteracyWorkparticipationRateAgriculturalLabourersCultivatorsMale Female Males Female Male Female Male Female29 Cheriyamundam 4248 28087 1138 931 76.1 72.9 33.0 2.9 13.9 12.0 5.7 6.730 Perumpadappa 4787 28208 1120 956 79.5 75.3 42.6 6.6 4.1 15.4 4.9 3.131 Ponmala 4662 28795 1067 947 76.8 73.4 38.5 4.1 17.8 19.7 10.8 6.832 Kuzhimanna 4877 28818 1024 983 77.6 71.4 42.5 6.0 20.4 23.5 12.6 8.433 Chokkade 5064 28887 1073 953 76.5 71.8 44.4 10.7 17.1 23.0 7.9 4.534 Chelambra 5223 28906 1032 988 81.8 76.7 46.2 4.1 10.8 10.9 1.9 0.835 Mankada 4964 28935 1048 995 81.7 78.8 46.2 7.7 30.3 37.4 11.6 5.836 Morayur 4899 29369 1006 960 78.6 73.5 40.5 3.9 20.9 21.0 7.5 5.237 Veliyankode 4928 29596 1109 938 79.3 73.9 45.2 7.8 8.8 20.1 3.5 3.438 Vettom 4462 29703 1135 1019 78.4 74.1 47.1 5.4 2.5 12.7 1.5 2.039 Ozhur 4778 29836 1114 992 75.8 70.3 38.6 3.7 16.1 15.2 8.0 6.940 Alamcode 5412 30118 1097 937 78.7 74.4 43.4 9.7 14.2 35.4 8.5 7.141 Edappal 5426 30292 1102 990 81.9 77.2 45.9 10.3 11.1 34.4 6.2 8.442 Edayoor 4867 30462 1072 976 75.6 71.0 41.4 5.4 21.0 28.1 6.1 3.043 Talakkad 5023 30577 1143 1023 78.6 74.4 40.7 4.3 6.2 11.7 3.1 2.544 Purathur 4931 30602 1100 988 78.2 72.7 46.0 6.3 4.8 17.7 3.6 4.845 Valavannur 4779 30615 1133 979 77.3 73.7 33.7 2.6 17.6 18.1 11.5 11.046 Peruvallur 4789 30624 1041 1007 76.1 68.5 40.4 4.1 22.3 42.9 6.4 3.147 Mambad 5589 30730 1052 966 77.5 72.3 44.4 8.7 19.5 31.9 6.0 3.948 Cherukavu 5547 30875 1011 928 80.4 75.8 46.3 6.3 8.3 9.2 2.9 2.949 Kalikavu 5454 30934 1093 971 76.6 71.7 43.2 7.8 18.4 35.2 8.0 3.950 Koottilangadi 5163 31147 1015 937 80.3 78.2 42.6 5.0 13.2 24.3 5.7 3.751 Kalpakancheri 5018 31263 1112 952 77.5 73.7 34.4 3.5 9.9 3.1 9.8 9.352 Vazhakkad 5563 31290 1018 952 81.1 75.8 43.3 5.0 16.0 21.6 6.8 8.153 Amarambalam 6182 31374 1064 931 77.8 72.4 47.6 12.7 15.9 30.4 6.1 3.254 Moorkkanad 5156 31488 1082 969 75.6 70.8 43.1 7.4 26.3 40.4 9.4 6.455 Kavanoor 5411 31538 996 975 77.6 71.2 43.4 5.6 25.0 36.9 10.2 5.856 Keezhattur 5580 31604 1084 936 78.7 75.9 45.1 9.7 25.5 39.0 12.4 10.757 Vattamkulam 5762 31635 1079 952 80.3 76.3 46.2 10.9 17.6 35.4 7.7 11.458 Parappur 4922 31775 1078 926 78.5 75.4 38.1 4.3 8.8 4.6 6.3 3.259 Pookkottur 5198 31832 1003 962 77.7 72.8 41.7 4.1 22.6 29.4 10.5 7.460 Marancheri 5597 31846 1121 934 80.7 76.0 43.1 6.7 10.8 32.9 4.5 2.661 Kodur 5245 32375 1052 969 80.5 77.3 39.9 2.8 10.6 15.4 8.6 4.362 Chungathara 6701 33017 1050 930 78.6 74.8 48.4 12.0 26.8 38.5 10.6 2.421

SlNoPanchayatNo. ofHouseholdsTotalPopnSexratioofPopnSexratio0-6PopnLiteracyWorkparticipationRateAgriculturalLabourersCultivatorsMale Female Males Female Male Female Male Female63 Pulamanthole 5763 33917 1116 934 79.3 76.2 41.8 8.6 27.9 43.7 8.9 11.664 Marakkara 5703 34573 1110 935 74.7 71.7 38.0 5.9 15.8 18.6 8.3 9.065 Kannamangalam 5411 34753 1043 871 75.1 70.8 37.8 3.9 11.8 20.6 6.8 5.766 Othukkungal 5439 34882 1074 961 77.4 74.7 39.3 2.7 9.0 10.7 6.7 2.667 Pulikkal 5666 35050 1005 942 78.9 73.1 38.7 5.0 16.1 13.4 7.3 5.468 Pulpatta 5982 35093 1018 964 77.4 72.1 41.8 6.2 30.4 35.9 11.6 7.469 Urangattiri 6580 35136 1014 986 77.6 71.9 45.7 8.3 26.9 42.0 7.5 7.270 Nannambra 5404 35532 1109 953 75.1 70.0 36.4 3.2 9.8 22.1 5.0 3.971 A R Nagar 5434 35534 1059 984 78.4 72.4 37.7 2.9 12.9 18.6 4.9 8.372 Valanchery 5926 35795 1047 934 79.4 76.0 41.0 5.9 8.9 16.4 5.3 3.273 Mangalam 5147 36283 1103 905 73.5 70.6 44.6 5.0 5.9 13.5 2.3 3.474 Thazhekode 6046 36548 1084 993 75.1 70.1 41.7 7.4 34.7 46.6 13.0 4.575 Karuvarakundu 6506 36956 1083 1007 78.7 73.0 46.3 10.9 9.8 9.8 4.6 3.276 Aliparamba 6214 37038 1065 955 78.1 75.1 45.4 8.7 31.1 39.3 11.9 6.377 Triprangode 5935 37175 1134 963 79.0 75.3 41.2 5.6 10.6 30.7 6.0 5.678 Athavanad 5857 38032 1026 964 77.8 72.6 36.6 4.5 14.0 19.1 7.8 6.979 Pallikkal 6344 38166 1015 920 78.5 73.8 41.5 3.8 11.1 13.9 5.8 2.680 Kuruva 6249 38927 1048 910 77.4 73.4 40.9 6.0 19.5 39.6 9.3 3.781 Kottakkal 6791 39554 1079 983 79.3 75.8 40.9 5.1 7.8 6.6 5.4 1.682 Edavanna 6809 39818 1027 996 79.2 73.7 44.9 7.2 28.8 43.5 8.1 3.383 Tanalur 6483 40884 1092 977 79.2 74.8 39.6 3.2 6.5 11.1 2.3 2.584 Nilambur 8009 41264 1040 958 81.8 77.6 46.9 11.2 9.9 15.6 3.5 2.485 Vallikkunnu 7521 41840 1069 965 81.2 76.0 47.8 6.1 6.6 7.4 2.8 2.286 Wandoor 7875 42487 1050 945 77.8 72.7 46.5 11.4 22.2 42.5 8.4 5.887 Thirunavaya 6662 42502 1139 1008 77.3 72.5 36.8 3.9 13.7 20.7 6.3 4.188 Kuttippuram 7135 43173 1083 979 79.6 75.2 42.8 6.9 8.1 24.2 5.2 4.989 Anakkayam 7535 43284 1052 986 79.4 77.1 44.8 5.5 20.6 29.2 9.8 4.690 Vengara 6740 43904 1102 970 76.4 70.9 35.9 2.5 13.5 18.3 6.0 2.891 Vazhikkadavu 8308 44083 1071 977 77.7 72.8 45.0 11.6 36.8 44.6 12.4 8.692 Trikkalangode 7817 44240 1027 951 79.1 75.1 46.3 9.3 41.8 58.8 9.5 5.093 Moonniyur 7477 47372 1043 917 77.7 71.7 41.3 5.3 10.0 16.9 4.9 4.094 Pandikkad 8320 47856 1061 989 76.8 72.9 44.2 9.2 26.6 41.7 13.1 7.695 Angadippuram 8961 48849 1071 962 80.8 78.1 44.2 7.6 24.4 22.6 8.3 4.822

SlNoPanchayatNo. ofHouseholdsTotalPopnSexratioofPopnSexratio0-6PopnLiteracyWorkparticipationRateAgriculturalLabourersCultivatorsMale Female Males Female Male Female Male Female96 Cheekkode 8432 50532 1019 971 78.3 72.2 40.6 4.2 25.5 29.4 7.9 7.097 Tirurangadi 7576 50612 1061 924 79.3 74.0 39.0 3.7 4.9 11.3 2.9 3.198 Tavanur 9686 53614 1095 949 78.7 73.9 46.4 10.1 14.2 34.9 7.3 5.999 Parappanangadi 9782 62781 1070 943 77.1 72.1 44.6 4.5 6.0 9.8 1.9 1.5100 Tanur 9006 63208 1068 1000 75.0 68.0 47.4 3.7 3.4 6.7 1.7 4.1With regard to literacy rate, it is found that, male literacy is least in MangalamPanchayat (73.5 percent) and female literacy is least in Tanur (68 percent)panchayat. But Vazhayur panchayat stands out from the rest for having highestmale (83.7 percent) and female literacy (79.5 percent).Information on Work Participation rate (WPR) as furnished in Table 2.2 revealsthat Male and female WPR varies between a low of 32.5 percent and 1.7 percentrespectively in Thennala panchayat and a high of 51.3 percent and 16 percentrespectively in Chaliyar panchayat. Its obvious that female WPR is quite low inthe panchayats. Among those employed in some kind of work (both Mainworkers and Marginal Workers), the proportion of male Agricultural labourersvaries between a low value of 2.5 percent in Vettom panchayat and high of 41.3percent in Thrikalangode panchayat. The corresponding variation with regard tofemales is between 3.5 percent in Kalpakancherri and 65.9 percent in Edapattapanchayat. The proportion of Cultivators is still less. The proportion of Malesand Females employed in Cultivation is highest in Vettathur panchayat (17.1 and14.8 percent respectively) whereas, the least proportion of male and femalecultivators are seen in Vettom (1.5 percent) and Tenhippalam (0.7 percent)panchayat respectively.Malappuram district has 5 municipalities the most populous one being PonnaniMunicipality (87495 lakhs) (Table 2.3). Perinthalmanna (44612 lakhs) is the least23

populated among them and the other three are Manjeri (83707 lakhs),Malappuram (58491 lakhs) and Tirur (53654 lakhs). The overall sex ratio in themunicipalities is favourable to females with Ponnani having the highest sex ratio(1100) and least in Manjeri (1022).The sex ratio of 0-6 population is however favourable to males in all the 5municipalities. As regards education, around 80 percent of the males are literatein all 4 municipalities except Ponnani with male literacy of 76.1 percent. Femaleliteracy varies between 78.5 percent in Perinthalmanna and 70 percent inPonnani.With regard to work participation rate, it can be said that, when about 40 to 45percent of the males are economically active, only less than 10 percent of thefemales are engaged in some kind of work. Due to the urban settings, theproportion of agricultural labourers and cultivators are quite less in thesemunicipalities.Table 2.3: Municipality Population, Malappuram, 2001SlNoMunicipalityNo. ofHouseholdsTotalPopnSexratioofPopnSexratio0-6PopnLiteracyWorkparticipationRateAgriculturalLabourersCultivatorsMale Female Males Female Male Female Male Female1 Manjeri 14717 83707 1022 959 80.3 77.7 44.3 6.7 3.2 1.5 11.7 15.32 Malappuram 10353 58491 1041 962 80.9 78.2 42.3 6.8 3.2 1.0 5.5 5.93 Perinthalmanna 8093 44612 1076 935 80.7 78.5 45.6 9.9 3.1 1.1 11.7 20.04 Tirur 8558 53654 1069 925 80.5 77.7 40.4 5.4 0.9 0.2 3.8 1.75 Ponnani 12990 87495 1100 940 76.1 70.0 43.7 4.9 0.6 1.0 2.1 5.524

Figure 2.1: Panchayat Wise Population of Malappuram District, 200125

2.2 Estimation of FertilityGiven the demographic profile of the panchayats and the municipalities, we nowturn on to the estimation of fertility of these panchayats. Demographic researchso far has developed many indirect methods of fertility estimation based on thedata available from different sources. A common and widely used method ofestimation of fertility that requires minimum available data is the reverse survivalmethod of fertility estimation. This basis of this method is estimation of numberof births occurring ‘x’ years before enumeration from the enumerated populationaged ‘x’ years. Here we estimate the number of births occurring during the sixyears immediately preceding the census year 2001, that is the period 1994-2001,from data on children aged 0-6 years as enumerated by the 2001 Census. Yetanother important aspect in this method of estimation is the availability of lifetable. Adequate information allowing the direct construction of reasonable lifetables is lacking in most countries where reverse-survival estimates of fertilityare needed. The usual practice is to rely on the Model life tables constructed bythe United Nations and the Coale and Demeny Model life Tables. However inIndia, the Sample Registration System publishes annually life tables annuallybased on average age specific death rates for the past three years and we use thelife table constructed for the year 2000 for the state of Kerala. Here an importantassumption made is that the mortality situation prevailing in the Panchayatsconforms to that prevailing in the state since non-availability of age specificdeath rates at the Panchayat level does not allow the construction of life tables.The following data are required for this method:(a) The population aged 0-6 years;(b) The total population 10 years apart, that is during the enumeration 2001 andpreceding census 1991, inorder to estimate the growth rate; and(c) Life Tables to estimate the survivorship probabilities.26

The growth rate ‘r’ is estimated asr = ln [P1/P0 ] /(t1-t0)where P1 is the population during t1 (2001) and P0 is that during t0 (1991);The mid year population Pm is then estimated asPm = Po exp[r(tm-t0)]Now the number of births is estimated asB = 0P6 / 0S6where 0P6 is the population aged 0-6 years and 0S6 is the survival probabilityfrom birth to 0-6 years estimated from the life table for Kerala estimated by ‘TheRegistrar General of India’ and as given in the Sample Registration Systemduring the year 2000.In any life table, the death rates are assumed to be uniformly distributed. TheSRS abridged life tables gives the number of deaths as 1d 0, 4d 1, 5d 5 etc. To get thedeaths for the ages 5 and 6 years, we divide 5d 5 by 5 and multiply by 2considering the uniform distribution of deaths assumption. From this value weestimate lx values for the ages 5 and 6. To get the survival rate or 0S 6 we divide0l 6 by 7l 0 .The birth rate ‘b’ is estimated asb = B / PmThe birth rate thus estimated for all the Panchayats in the Malappuram district isgiven in the following Table 2.4. The estimated birth rates are further classifiedusing the statistical technique of cluster analysis. From the different clusters thatthe cluster analysis yields, the panchayats are classified as those with birth ratebelow the district average of 23.3 births per 1000 population and those above thedistrict average. One panchayat stands out from the rest and forms an outlier.This outlier is Pookkottur panchayat of Malappuram block in Ernad Taluk with abirth rate of 27.8. This is the panchayat with the highest birth rate. At the other27

extreme, birth rate is least in Perumpadappu panchayat of Ponnani Taluk. Table2.5 shows the panchayats with birth rates above the district average of (23.4 to26.1) to be mainly concentrated in the Ernad and Tirurangadi taluks. Nilambur,Perinthalmanna and Tirur taluks also have a few panchayats with higher birthrates. This includes 15 panchayats of Ernad, 10 of Nilambur, 9 ofPerinthalmanna, 7 of Tirur and 11 panchayats of Tirurangadi. Among thepanchayats with birth rate lower than the district average, Ponnani taluk standsout from the lot in the sense that all the panchayats have very low birth rateranging from 18.4 to 20.6.Table 2.4: Birth Rate of Panchayats in Malappuram district, 1996-2001Name of Taluk Name of Block No. ofPanchayatsName ofPanchayatsBirthrateMALAPPURAM: Birth Rate = 23.3Ernad Areacode 7 Areacode 23.9Cheacode 24.9Kavanur 25.4Keezhuparamba 24.3Kuzhimanna 25.3Pulpatta 26.1Urngattiri 24.6Kondotty 8 Chelembra 21.6Cherukavu 22.7Kondotty 25.2Nediyiruppu 25.1Pallikal 24.7Pulikkal 24Vazhakkad 22.2Vazhayoor 20.6Malappuram 6 Anakkayam 25Kottakkal 22.3Morayur 25Oorakam 24.9Ponmala 25.8Pookkottur 27.828

Name of Taluk Name of Block No. of Name ofBirth ratePanchayats PanchayatsPerinthalmanna Mankada 9 Angadipuram, 22.1Kodur 24Koottilangadi 24.9Kuruva 24.2Mankada 23Makkaraparamba 23.2Moorkanad 23.8Pulamanthole 22.8Puzhakkattiri 22.9Perinthalmanna 7 Aliparamba 23.6Edapatta 23.9Elamkulam 21.7Keezhattur 22.3Melattur 23.5Thazhekode 25Vettathur 24.2Ponnani Perumbadappu 5 Alancode 20.2Maranchery 18.8Nannamukku 19.5Perumpadappu 18.4Veliyancode 18.8Ponnani 3 Edappal 18.9Thavanur 20.6Vattamkulam 20.3Tirur Tanur 9 Cheriyamundam 23Kalpakanchery 24.7Niramaruthur 22.1Ozhur 23Perumanna Klari 23.4Ponmundam 22.7Tanalur 21.4Tanur 24.7Valavannur 23.7Tirur 6 Mangalam 22.1Purathur 19.6Thalakkad 21.7Thirunavaya 22.3Triprangode 21.4Vettam 2129

Name of Taluk Name of Block No. ofName of Panchayats Birth ratePanchayatsTirur Kuttipuram 6 Athavanad 23.7Edayur 25.2Irimbiliyam 21.4Kuttippuram 21.6Marakkara 25.3Valanchery 23.1Tirurangadi Tirurangadi 7 Moonniyur 25.1Nannambra 25.1Parappanangadi 24.5Peruvallur 24.2Tenhipalam 19.4Tirurangadi 23.7Valikunnu 21.1Vengara 7 A.R.Nagar 24.8Edaricode 23.2Kannamangalam 24.1Othukkungal 26.1Parappur 24.9Thennala 24.6Vengara 24.2Nilambur Nilambur 11 Amarambalam 22Chaliyar 22.4Chokkad 23.8Chungathara 19.8Edakkara 21.1Kalikavu 23.5Karulai 23.6Moothedam 23.2Nilambur 20.6Pothukallu 21Vazhikadavu 22.2Wandoor 9 Edavanna 24.7Karuvarakundu 22.8Mambad 25Pandikkad 25.1Porur 24.7Thiruvaly 21.3Thrikkalangode 24.2Thuvvur 23.6Wandoor 23.930

Municipalities Birth RateManjeri 23.9Perinthalmanna 22.1Malappuram 23.8Tirur 21.0Ponnani 24.0Note: During the 1991-2001 decade, 6 more panchayats have been added to the 94panchayats in 1991. For those panchayats from which the new panchayats have beencarved out and also the newly formed panchayats, the population in the year 2001 hasbeen used in place of mid year population as the jurisdictional changes have not beenaccounted.Tirur taluk is also better placed in this regard as 14 panchayats have birth ratebelow the district average.10 panchayats of Nilambur taluk, 7 ofPerinthalmanna taluk, 5 panchayats of Ernad and 3 of Tirurangadi taluk havebirth rate below 23.Table 2.5: Classification of Panchayats by birth rate into different clustersTaluk Panchayat Taluk PanchayatBirth Rate 23.4 to 27.8 Birth Rate 18.4 to 23.2Ernad 1. Pookkottur Ernad1. Chelambra(27.8)20.6 to 22.7 2. CherukavuErnad1. Anakkayam 3. Kottakkal23.9 to 26.1 2. Areekode 4. Vazhakkad3. Cheekkode 5. Vazhayur4. Kavanoor Nilambur 1. Amarambalam5. Kizhuparamba 19.8 to 23.2 2. Chaliyar6. Kondotty 3. Chungathara7. Kuzhimanna 4. Edakkara8. Morayur 5. Karuvarakundu9. Nediyiruppu 6. Moothedam10. Pallikkal 7. Nilambur11. Ponmala 8. Pothukallu12. Pulikkal 9. Thiruvali13. Pulpatta 10. Vazhikkadavu14. Urakam Perinthalmanna 1. Angadippuram15. Urangattiri 21.7 to 23.2 2. ElamkulamNilambur23.5 to 25.11. Chokkade 3. Keezhattur2. Edavanna 4. Makkaraparamba3. Kalikavu 5. Mankada4. Karulai 6. Pulamanthole5. Mambad 7. Puzhakkattiri31

Taluk Panchayat Taluk PanchayatBirth Rate 23.4 to 27.8 Birth Rate 18.4 to 23.2Nilambur 6. Pandikkad Ponnani 1. Alamcode23.5 to 25.1 7. Porur 18.4 to 20.6 2. Edappal8. Thuvvur 3. Marancheri9. Trikkalangode 4. Nannamukku10. Wandoor 5. PerumpadappaPerinthalmanna 1. Aliparamba 6. Tavanur23.5 to 25.0 2. Edappatta 7. Vattamkulam3. Kodur 8. Veliyankode4. Koottilangadi Tirur1. Cheriyamundam5. Kuruva 19.6 to 23.1 2. Irimbiliyam6. Melattur 3. Kuttippuram7. Moorkkanad 4. Mangalam8. Thazhekode 5. Niramaruthur9. Vettathur 6. OzhurTirur23.4 to 25.3Tirurangadi23.7 to 26.11. Athavanad 7. Ponmundam2. Edayoor 8. Purathur3. Kalpakancheri 9. Talakkad4. Marakkara 10. Tanalur5. Perumanna Clari 11. Thirunavaya6. Tanur 12. Triprangode7. Valavannur 13. Valanchery1. A.R Nagar 14. Vettom2. Kannamangalam Tirurangadi 1. Edarikode3. Moonniyur 19.4 to 23.2 2. Thenhippalam4. Nannambra 3. Vallikkunnu5. Othukkungal6. Parappanangadi7. Parappur8. Peruvallur9. Thennala10 Tirurangadi11. Vengara2.4 Application of Geographic Information SystemGeographic Information System (GIS) is an information system designed to workwith data referenced by spatial / geographical coordinates. In other words, GIS32

is both a database system with specific capabilities for spatially referenced dataas well as a set of operations for working with the data. It may also be consideredas a higher order map. GIS technology integrates common database operationssuch as query and statistical analysis with the unique visualization andgeographic analysis benefits offered by maps. These abilities distinguish GISfrom other information systems and make it valuable to demographic analysis, inparticular, for explaining events, predicting outcomes, and planning strategies.Here the estimated fertility rates of Malappuram district are represented asthematic maps using GIS Software. Since information on sex ratio, workparticipation rate and literacy are available for each panchayat; a few maps aregenerated that should possibly explain the association between these variablesand fertility if any.Figure 3 shows the panchayat wise birth rate classified in 5 groups. The lowbirth rate (represented in blue colour) in most of the panchayats of PonnaniTaluk is quite evident. Chungathara panchayat of Nilambur taluk, Purathur ofTirur taluk and Thenjipalam of Tirurangadi taluk also stands out from the rest ofthe panchayats with low birth rate. The other panchayats that have birth ratebelow the district average (represented in green and yellow colours) are mostlyfrom Tirur, Nilambur and Perinthalmanna taluks. Those Panchayats with birthrates on the higher side (represented in orange and pink colours) are scatteredmostly in Ernad, Tirurangadi and Nilambur taluks.33

Figure 3: Panchayat wise Birth Rate, Malappuram (1996-2001)34

The influence of socio economic, cultural and demographic factors on fertility is awidely proven aspect. Here an attempt is made to learn the possible associationof factors like literacy and work participation rate on fertility. In Malappuramdistrict only one panchayat, Kavannur of Ernad taluk, shows sex ratio favourableto males. Though association between sex ratio and fertility cannot beestablished, Figure 4 shows that in panchayats with low fertility, sex ratio is onthe higher side (also greater than the state average). Panchayats with high birthrate on the contrary shows low sex ratio.Education is an important variable that affects the fertility of a population. Theinverse relationship between literacy and fertility is an undisputed fact. Thisassociation is found to be true to a certain extent in Malappuram district. Keralaenjoys the position of being the most literate state and hence the districts toohave literacy on the higher side. Panchayat wise literacy rate in Malappuramvaries between 71 and 82 percent. Male literacy varies between 73.5 and 83.7percent and that of females varies between 68 and 79.5 percent. Figure 5portrays the inverse association between literacy and birth rate though withexceptions. Most of the low fertility panchayats have high literacy rate and someof the high fertility panchayats have low literacy rates. Ponnani taluk and somepanchayats of Tirur taluk, Chungathara and Thenjipalam panchayat etc with lowfertility are examples of low fertility panchayats with high literacy rate. On theother hand, most of the panchayats with high fertility from Ernad and Nilamburtaluk are instances of high fertility populations under conditions of low literacy.Work Participation rate and the associated economic opportunities have a strongbearing on the fertility levels of a population. Agriculture/Cultivation continuesto be the main source of income to many people in the state. As variousdemographic theories hold, fertility is usually high among people who involve insuch occupation due to its seasonal nature. In Malappuram panchayats, the35

maximum percentage of agricultural workers to total workers adds up to about48 percent and that of cultivators to about 20 percent. While examining theassociation between birth rate and proportion of total workers in each panchayat(Figure 6), birth rate is generally high in panchayats with low work participationrate and vice verse though there are many exceptions to this observation. But ifthe association between the proportion of agricultural workers and fertility leveland that of proportion of cultivators and fertility are examined, a positiveassociation is discernible in both cases. In some of the panchayats with higherproportion of agricultural workers, birth rate is also high as in the case ofVazhikadavu, Thazhekkode, Pozhur, Pandikad etc. The panchayats with lowproportion of cultivators and low birth rate are mostly in Ponnani Taluk, andsome panchayats in Nilambur Taluk. Examples of high fertility panchayats withhigher proportion of cultivators, though a few, are Vazhikkadavu, Pulpatta,Pookkottur, Kuzhimanna etc.36

Figure 4: Panchayat Wise Birth Rate and Sex Ratio of Malappuram District,200137

Figure 5: Panchayat Wise Birth Rate and Literacy of Malappuram District, 200138

Figure 6: Panchayat Wise Birth Rate and Distribution of Total Workers ofMalappuram District, 200139

Figure 7: Panchayat Wise Birth Rate and Distribution of Agricultural Workersof Malappuram District, 200140

Figure 8: Panchayat Wise Birth Rate and Distribution of Cultivators ofMalappuram District, 200141

Chapter IIIDeterminants of FertilityFertility in Kerala touched replacement levels during 1987 when the TotalFertility Rate (TFR) declined to 2.1 or the Net Reproduction Rate (NRR) equaledone. The factors that contributed to this decline are myriad. Nair (1974),Krishnan (1976), Ratcliffe (1978) and Nair (1986) attributed the observed declinein fertility in Kerala to factors like female education, land reforms, matriarchalsystem of family inheritance and strong political will and leadership thatimproved social welfare services. One argument put forward in explaining thisdecline is a well organized family planning program and its successfulacceptance in the state (Kurup and Cecil 1976). Yet another factor as suggestedby Krishnan (1976) is the changes in nuptiality brought about by improvement infemale education. Zachariah’s (1984) study, based on the World Bank FertilityStudy (1980) in the three districts of Kerala showed that the underlying factorsfor fertility decline were a series of socio-economic changes – mainlyimprovements in health and education and also the success of family planningprogramme which strengthened the desire for smaller families. ImprovedMortality situation that prevailed in the state contributed to further decline infertility as survival of increasing numbers of children to adulthood broughtabout pressure on the economic resources in the families. Mortality decline hadbegun early in Kerala owing to the health care programs introduced by theTravancore and Cochin governments (Panikar 1975). Sushama, (1996) opined, onthe basis of her study in a Kerala village, that the proximate determinants of42

fertility decline were postponement of marriage and extensive use ofcontraceptives accomplished as a result of changing socio-economic conditions.The district of Malappuram has been lagging behind most other districts in thestate in fertility transition. Zachariah et. al (1994) estimated the fertility rate inthree districts which included Malappuram. Their estimate using reversesurvival method (using survival ratios from South model Coale and DemenyModel Life Tables) puts CBR at 30.3 during 1981-86 and 27.8 during 1986-91. Therecent estimate by Guilmotto and Rajan (2002) shows that the CBR inMalappuram was 22.4 as against the national average of 17.1. Their estimate ofTFR in the district was 2.4 as against 1.7 for the state.The reason for the high fertility in Malappuram has been a subject of inquiry.Since fertility is in general found to be higher among the Muslims in Kerala, thereason for high fertility in Malappuram is attributed to the fact that Malappuramis a Muslim dominated area. However studies on fertility determinants in Keralashow that fertility in Malappuram is declining at a similar pace as in the case ofany other religion. Zachariah et. al (1994) opined that although fertility rate inMalappuram is relatively high, there was considerable improvement in thefertility situation in the district as the amount of decline in fertility was muchlarger than those in other districts. The levels remained high during the 1980sand 1990s due to the historic lag in the development process in the district.Studies also show that fertility transition among Muslims in India has beennearly at the same pace as that of Hindus (James and Nair, 2005) and theobserved religion wise difference in fertility is only due to a time lag in initiationof decline. So here the factors that contribute to decline in fertility levels inMalappuram district are examined in the following section.43

The data used for the analysis pertain to the Reproductive and Child HealthSurvey Round II, Phase I and II, 2004 carried out in all the 14 districts of Kerala.Multiple Classification Analysis (MCA) is used to study the nature andmagnitude of association of different socio-economic and demographic variableson children ever born among women in the district. The MCA is a special case ofmultiple regression with dummy variables. Given two or more inter relatedfactors; it is a valuable tool to know the net effect of each variable when thedifferences in the other factors are controlled for. We employ MCA here as itprovides the grand mean number of children ever born and a set of categorymeans for each factor expressed as deviations from the grand mean as maineffects. Children ever born (CEB) is the dependent variable and women’sselected background factors are the independent variables. The results show thesole effect of each factor on fertility, when the influences of other intermediatefactors are controlled. The variable woman’s marital duration is taken as acovariate. The rationale for taking marital duration as covariate concurrentlywith the explanatory variables is that it helps in understanding the effect ofwomen’s background socio-economic and demographic factors on fertility afteradjusting for differentials in fertility caused on account of this variable. Thehierarchical analysis is opted as it gives the effect of a particular variablecontrolling for the effects of all the preceding variable(s) and the covariates takenas the adjusted values.To get an idea about the number of children that women from different socioeconomic and demographic settings have, children ever born are classified inthree classes. Since the mean number of children ever born to women inMalappuram is 2.56, the bivariate classification of CEB by backgroundcharacteristics are examined for those women with 1 child, 2 children and 3 ormore children.44

When CEB is classified by age of women, it is found that more than one-third ofthe women (38 percent) in the prime reproductive age groups of 20-24 years,who are yet to complete their child bearing, already have 2 children and about 14percent have 3 or more children. Similarly among women in the 25-29 year agegroup, 42.2 percent have 2 children and an almost equal proportion of womenhave 3 or more children. The estimated figures for mean age of mother at 2 ndand 3 rd order birth are about 21.8 years and 24.4 years respectively.So earlymarriage and early childbearing pattern among women in Malappuram coupledwith low contraceptive prevalence rates attributes to the high fertility ratescompared to other districts of Kerala.Table 3.1: Women classified according to the Children ever born and theirbackground characteristicsVariablesChildren ever born1 2 >=3Age of women 15-19 years 75.0 (33) 18.2 (8) 6.8 (3)20-24 years 48.4 (93) 38.0 (73) 13.5 (26)25-29 years 15.1 (28) 42.2 (78) 42.7 (79)30-34 years 4.7 (9) 27.9 (53) 67.4 (128)35-39 years 2.8 (4) 14.0 (20) 83.2 (119)40-44 years 7.1 (8) 13.4 (15) 79.5 (89)Residence Rural 19.8 (158) 28.3 (226) 52.0 (416)Urban 25.8 (17) 31.8 (21) 42.4 (28)Religion Muslims 21.3 (140) 26.1 (171) 52.6 (345)Others 16.7 (35) 36.2 (76) 47.1 (99)Caste OBC 20.7 (155) 27.0 (202) 52.2 (390)Others 16.8 (20) 37.8 (45) 45.4 (54)Standard ofLivingAge atConsummationof marriageMaritalDurationLow 11.1 (15) 28.9 (39) 60.0 (81)Medium 21.9 (113) 27.7 (143) 50.5 (261)High 22.0 (47) 30.4 (65) 47.7 (102)=18 years 28.8 (84) 34.2 (100) 37.0 (108)0-4 years 79.5 (101) 18.1 (23) 2.4 (3)5-9 years 25.3 (49) 51.5 (100) 23.2 (45)10-14 years 5.4 (10) 38.9 (72) 55.7 (103)15+ years 4.2 (15) 14.4 (52) 81.4 (293)45

VariablesEducation ofwomenEducation ofHusbandHealth WorkervisitContraceptivePrevalence RateAwarenessabout modernspacingmethods of FPAwarenessabout Allmodernmethods of FPChildren ever born1 2 >=3Non-literate 4.7 (2) 18.6 (2) 76.7 (33)0-9 years 17.4 (123) 28.9 (204) 53.7 (380)10+ years 43.1 (50) 30.2 (35) 26.7 (31)Non-literate -- 22.2 (10) 77.8 (35)0-9 years 19.2 (130) 28.3 (192) 52.5 (356)10+ years 32.4 (45) 31.7 (44) 36.0 (50)Yes 21.4 (31) 32.4 (47) 46.2 (67)No 20.0 (144) 27.7 (200) 52.3 (377)Using 11.2 (56) 24.5 (123) 64.3 (323)Not Using 32.7 (119) 34.1 (124) 33.2 (121)Yes 20.3 (162) 29.1 (232) 50.6 (404)No 19.1 (13) 22.1 (15) 58.8 (40)Yes 20.6 (95) 29.9 (138) 49.6 (229)No 19.8 (80) 27.0 (109) 53.2 (215)Distribution of CEB by type of residence, religion and caste shows somedifference. Among the rural women when 52 percent have 3 or more children,among the urban women, only 42 percent have 3 or more children. Among theMuslim women, more than half and among women of other religious groups, 47percent have 3 or more children. Similarly among OBC caste 52 percent andamong other caste women, 45.4 percent have 3 or more children.The influence of standard of living on fertility is expected to show an inverserelationship in any population group. This inverse relationship is visible in thepresent sample of women of Malappuram district. Among women in the lowstandard of living category, 60 percent of the women have 3 or more than 3children whereas, among those women in the high standard of living category,less than half of the women only had 3 or more CEB.46

The direct effect of age at marriage on CEB is evident here. Among those womenwho marry early (< 18 years), 57.5 percent have 3 or more CEB in contrast tothose women who have age at consummation of marriage more than 18 years, 37percent of whom only have CEB as 3 or more. With regard to marital duration,as expected, CEB increases as marital duration increases.Education of the respondent and also that of their husband shows negativerelationship with the number of children ever born. Among illiterate women,more than three-fourths have 3 or more children. Majority of the women in thesample have 0-9 years of schooling and among them more than half have 3 ormore children and among those with 10 and more years of schooling, only aquarter falls in this category. Education of husband also shows similar influenceon the number of CEB to women.Visit by health worker and the advise provided to the people on family planningmatters is important in the successful acceptance of Family PlanningProgrammes especially fertility control measures adopted by the couples.Though health worker visit to households is less in the present sample itsimportance is highlighted here as it is found that less than half of the womenwho have been visited by health workers have on an average 3 or more childrenin contrast to those women who have not been visited by Health Workers andamong whom almost two thirds have 3 or more children.With regard to use of contraceptives and the number of CEB, its usually foundthat women tend to adopt some method either after they achieve their desiredfamily size or to maintain spacing between births. In the present sample, 58percent of the women are reported to be currently using contraceptives. Amongthem a quarter of them have 2 children, and more than two-thirds have 3 ormore children. This is a much expected result as women of higher parity tend to47

adopt different methods more. Among non users the proportion of women with1 child, 2 children and 3 or more are almost equally distributed.Awareness about modern contraceptive methods especially modern methodsincreases contraceptive use rate. In the present sample we see that half of thosewomen who have heard of modern spacing methods have and nearly two-thirdsof those women who have not heard about these methods have 3 or more CEB.Similarly among those who have heard about all modern methods of FamilyPlanning, nearly 50 percent have 3 or more children as against 54 percent amongthose unaware of all modern methods.These findings reveal how the number of CEB to women varies by their socioeconomicand demographic background characteristics. To know which of thesevariables form significant predictor variables of fertility or to bring out the soleeffect of each factor on fertility, when the influences of other intermediate factorsare controlled, we use the Multiple Classification Analysis.furnished in Table 3.2.The results areThe result of MCA for selected demographic and socio economic characteristicsfor all women shows that the Grand Mean of CEB is 2.56. The multiple R 2 was0.297 when all the independent variables were included. However this valueincreased to 0.551 when the covariates were included. This means that all theindependent variables together explains only 29.7 percent of the variation in thedependent variable CEB whereas, the independent variables together withcovariates explains 55.1 percent of the variations in the dependent variable CEB.48

Table 3.2 Results of Multiple classification analysisDependent Variable: CEB (Continuous)Covariate: Marital DurationGrand Mean CEB: 2.56, N= 888Variables withcategoryNUnadjustedMCEB EtaAdjusted forIndependentsMCEB BetaAdjusted forIndependents +CovariatesMCEB BetaReligionMuslims 674 2.62 2.64 2.45Others 214 2.46 2.32 2.230.07 0.09 0.12CasteOBC 767 2.59 2.58 2.57Others 121 2.38 2.45 2.510.05 0.03 0.01Standard of LivingLow 132 2.95 2.38 2.95Medium 529 2.54 2.52 2.54High 227 2.37 2.55 2.380.12 0.05 0.12Education of womenNon-literate 42 3.7 3.38 2.620-9 years 716 2.66 2.60 2.5510+ years 130 1.64 2.10 2.540.28 0.16 0.01Education of HusbandNon-literate 46 3.46 2.81 2.360-9 years 684 2.63 2.59 2.5910+ years 158 2.00 2.46 2.500.21 0.07 0.04Age at Consummationof marriage

Variables withcategoryNUnadjustedMCEB EtaAdjusted forIndependentsMCEB BetaAdjusted forIndependents +CovariatesMCEBBetaCurrent Use of FPMethodsUsers 383 1.91 1.7 2.07Non Users 505 3.05 3.21 2.930.36 0.49 0.28Unmet need for familyplanningYes 181 2.39 3.20 2.98No 707 2.52 2.40 2.450.06 0.21 0.14Multiple R 2 0.297 0.551Multiple R 0.545 0.742The MCA results show that fertility of Muslim women is higher than thosewomen belonging to other religious groups mainly Hindus and Christians.Muslim women in the present sample have on an average 2.5 children as againstthat of 2.2 children among other religious groups. Similarly women belonging toOBC category also have higher MCEB when compared to other caste category.The effect of standard of living on fertility is quite evident. Women who comeunder the low standard of living category have on an average 2.95 childrencompared to 2.38 children among those who enjoy high standard of living.Education of women as expected shows the inverse relationship with fertility.Here the MCEB values estimated after adjusting for independent variables andcovariates is more among the illiterates and decreases gradually with increasingeducational attainment. Illiterate women have borne 2.62 children while thoseeducated 10 or more years have borne 2.54 children. Husband’s education does50

not show this relationship with fertility. However, MCEB among women whosehusbands have less than 10 years is slightly larger than those with 10 or moreyears of schooling. Since in the present sample of women, the fertility amongwomen whose husbands are illiterates is lesser than that of women whosehusbands have more years of schooling, the expected inverse relationship ofeducation with fertility do not hold true.Age at marriage has a direct effect on fertility in terms of the exposure of womento childbearing years. Women marrying early have longer exposures tochildbearing years. In the present survey, information on age at consummationof marriage is provided rather than age at marriage. In Malappuram, with morethan two-thirds of the women marrying before the attainment of legal age atmarriage, the expected positive relation of fertility with age at marriage shouldbe true. Truly so, MCEB among women whose age at consummation of marriageis less than 18 years, computed after adjusting for independent variables andcovariates, is 2.63 compared to 2.42 among those women whose age atconsummation of marriage is 18 years or more.The effect of contraceptive use in reducing fertility is undisputedly anestablished fact. Once the couples achieve their desired family size, the usualpractice is to adopt a contraceptive method preferably a permanent one.Temporary methods are used either to delay or also to avoid a birth. As thefindings here suggest the difference in fertility levels are visible in Malappurambetween users and non users of contraceptives. In fact contraceptive useemerges as the most significant predictor variable affecting fertility in thisparticular model. The unadjusted MCEB for this category is 1.91 among users asagainst 3.05 among nonusers. The Eta value was also highest for this variable.Even after adjusting for independents and also independents and covariates thecategory means remains the same and the Beta values also does not show much51

variation. The adjusted values show that users of any contraceptive methodhave on an average only 2.07 children ever borne in contrast to 2.93 among nonusers. This again highlights the importance of use of contraceptives. It wasalready mentioned that couple protection rate is the least in Malappuram amongthe 14 districts of the state. So improved contraceptive use can necessarily paveway for much lower levels of fertility provided the family planning effortssucceeds in cutting through the cultural barriers associated with religion asMalappuram is a Muslim dominated district.For couples who wish to delay or avoid a birth, the obstacles to contraceptive useoften include lack of knowledge about methods or where to obtain services, andconcerns about the side effects of different methods. These are reflected in theproportion of women who have an unmet need for contraceptives. Findings heresuggest that women with unmet need for contraceptives have higher fertilitythan those who do not. The MCEB among women who have unmet need for allmethods is 2.98 as against 2.45 among those women who do not have unmetneed for contraceptives.So the multivariate analysis employed to learn the mechanism of association ofsocio economic and demographic factors on CEB among women in Malappuramdistrict gives an impression that religion and caste of women do explain somedifferentials in fertility levels. Besides, at the household level, the standard ofliving and at the social circle, education of women has some association onobserved fertility. Age at consummation of marriage also is also a predictorvariable. But use of contraceptives emerges as the best predictor variable inMalappuram.52

Chapter IVDeterminants of Contraceptive Use4.1 IntroductionWith 69 percent of the currently married women using any contraceptive methodas reported by the third round of NFHS (2005-06), Kerala is placed well abovethe national average (56 percent). This figure was an increase from 63.7 percentfrom1998-99 (NFHS-2). Among the permanent methods, female sterilizationdominated in India and Kerala is no exception to this phenomenon. Couplestend to adopt permanent methods as and when they achieve their desired familysize. The proportion of acceptors of female sterilization was 48.5 percent inKerala during 1998-99 (NFHS-2) and 48.7 percent during 2005-06 (NFHS-3).Users of modern temporary methods of contraception that include oralcontraceptives, intra-uterine devices, and condoms increased from 5.1 percent to8.6 percent over the period 1998-99 and 2005-06 (NFHS-2 and NFHS-3).The use or non use of contraceptives is determined by varying socio-economicand cultural factors in different regions. According to Srinivasan (1984), thestates in India with greater contraceptive use have generally achieved goodsocioeconomic modernization which generates higher levels of motivation. Ingeneral, the major factor that determines the acceptability of contraceptivesespecially permanent method of sterilization in the country is the number ofliving children a couple has and the number of sons (Rajaram, 1998; Rajaretnam,53

2000; Bhasin and Nag, 2002). While some studies attribute increased use ofcontraceptives to mass media (Bhat, 1996; Ramesh et.al, 1996), increased spousalcommunication (Kamal, 1999; Ghosh, 2001), son preference, education andwomen’s age (Gandotra and Das, 1990), other studies show that religion(Chacko, 1988; Goldscheider and Mosher, 1988; Reddy, 1996) and good access tohealth care (Aarokiasamy, 2002) as the major determinants of contraceptiveprevalence in a community. Research also shows that female sterilization isunlikely to contribute to further fertility decline (Pathak et al. 1998; Bongaartsand Greenhalgh 1985). Previous studies have found barriers to contraceptive useas the monetary and time costs of obtaining contraception (Lewis 1986; Janowitzand Bratt 1996), the social stigma of using contraceptives in an unsupportivesetting (Bongaarts and Bruce 1995; Nag 1984), lack of knowledge (Basu 1984;Chaudhury 2001) desire for more children (Kumar et al. 1999; Santhya 2004).Sushama (1996) in her study on fertility in a Kerala Village expressed the viewthat smaller families became advantageous because of decreasing agriculturalopportunities, expanded education and mortality decline. Apart from this whencontraceptives were made available with the implementation of the familyplanning program, and higher use of contraceptives could be attributed tofavourable conditions resulting from socio-economic changes. According to her,though cost was an important issue in desiring a small family, women alsodesired small families to overcome such practical inconveniences as performingday-to-day chores during the antenatal and postnatal periods. The absence ofanyone to care for the older children at the time of their mother’s delivery andpostnatal period had become a problem since nuclear families were a commonresidential pattern. Besides, other costs included those for the delivery of the firstand to some extent the second child. This meant that the husband or a member ofthe husband’s family had to help the women at the time of childbearing.54

The couple protection rate in Kerala during the year 2004 touched 72.1 percent.If the district wise variation is accounted for, the highest value is seen inThiruvananthapuram district (97.6 percent) and Malappuram recorded thelowest couple protection rate of 49.6 percent (Economic Review, 2006). Thepossible contributing factors that influence the observed low contraceptiveprevalence rate in Malappuram is evidently a topic of enquiry. Here we examinethe determinants of contraceptive use in Malappuram district using the RCHSurvey data, 2004.4.2 About the sample The following section gives a brief demographic andsocio economic profile of the sample women of Malappuram district selected forthe RCH survey. Information on women’s, age, place of residence, religion,caste, education standard of living, age at marriage and marital duration is givenin Table 4.1. In the present sample, more than two-thirds of the women are intheir prime reproductive age 20-34 years (63 percent). Those below 20 yearsaccount for 8.4 percent and those aged 35 years and above form 28.6 percent. Butmajority of the women hail from rural background (92.7 percent). SinceMalappuram is a Muslim dominated district, the religious distribution ofpopulation is classified as ‘Muslims’ and ‘Other’ religious groups. Here morethan three fourths of the women (76.0 percent) are Muslims and Hindus andChristians who come under the ‘Other’ religious category constitute only24percent.55

Table 4.1: Percentage distribution of women classified by their backgroundcharacteristicsVariables Percentage Variables Percentage Variables PercentageAge Place of residence Religion

With regard to the information regarding marriage of women the surveyprovides details only on age at consummation of marriage and the maritalduration. When the age at consummation of marriage is classified as those belowthe legal age at marriage of 18 years and those greater than or equal to 18 years, itis seen that 64.8 percent of the women had age at consummation of marriagebelow 18 years and the rest only 36.2 percent at or above 18 years of age. Thesefigures are pretty high for a state that claims of being the most literate state in thecountry. So its quite evident that majority of the women in Malappuram districtmarry before attaining the legal age at marriage. If the marital duration isexamined, 60 percent of the women had marital duration of less than 15 yearsand the rest 40 percent 15 years and above.With regard to the number of living children a woman had during the survey,the mean number of children of the sample women is 2.56. So the number ofchildren is classified as women with 3 of less and above 3 children. Such a breakup shows that 77.2 percent of the women have 3 or less than 3 children and therest which for about a quarter of women have more than 3 children.4.3 Contraceptive PrevalenceThe level of use contraceptive methods is one of the proximate variables affectingfertility. Among the districts in Kerala, Malappuram district shows the leastvalue of couple protection rate. The information discernible from the presentsurvey on contraceptive use patterns are presented in Tables 4.2 and 4.357

Table 4.2: Contraceptive Prevalence RateCurrent use of Frequency PercentagecontraceptivesUsers 508 56.9Non users 385 43.1Table 4.3: Type of Contraceptive methods usedMethod TypePercentageFemale Sterilization 59.6Male Sterilization 0.4IUD/Cu-T/Loop 4.5Oral Pills 1.6Condom / Nirodh 4.3Rhythm / Periodic abstinence 24.8Withdrawal 1.0Other modern method 0.8Other traditional method 3.0Among the currently married women, 56.9 percent of the women are currentusers of family planning methods (Table 4.2). Among the users (Table 4.3),female sterilization dominates (60 percent). Users of IUD/CuT/Loop count up to4.5 percent, Condom/Nirodh to 4.3percent and Oral Pills are used by only 1.6percent of the women. A quarter of the women in the sample (25.8 percent) arestill users of traditional methods of withdrawal and safe period where the rate ofrisk of conception is pretty high.58

Table 4.4: Unmet Need for Family PlanningUnmet Need for FP MethodsLimiting Methods 7.0Spacing Methods 11.6All Methods 18.6Unmet need for contraceptive speak of the access and availability ofcontraceptive methods. Table 4.4 shows that, in the present sample, 18.6 percentof the women in Malappuram district have unmet need for contraceptives ofwhich, 7 percent are for limiting methods and 11.6 percent are for spacingmethods.4.3.1 Background characteristics of women currently using contraceptivesTable 4.5 draws some inference on the women who are currently using anycontraceptives classified by their background characteristics. With regard to ageof women, it can be inferred that the older cohort are more users ofcontraceptives than the younger ones who are in their prime reproductive agegroups. This is of course an expected trend as women tend to go forcontraceptives mostly limiting methods once they achieve their desired familysize. When 28 percent of the women aged less than 20 years are users ofcontraceptives, 52.6 percent of those in the 20-34 year age group and 74.9 percentof those aged 35 years and more are users of family planning methods (χ 2significance at 1% level) .Urban women, though less in number in the present sample, are seen to be usingcontraceptives more than that of their rural counterparts (67.7 percent as against56 percent respectively with χ 2 significance at 5% level). As regards religion,lesser proportion of Muslim women (50.2 percent) use contraceptives comparedto women in other religions (78 percent) and the finding is significant at 1% level.59

Similarly women belonging to OBC category are lesser users of family planningmethods compared to those in the other caste category (54.4 percent as against72.7 percent respectively). Earlier studies based on analysis of NFHS-1 data alsosuggest that religion has a substantial effect on contraceptive use, even aftercontrolling for education, and that Muslims have lower use rates than Hindus(Ramesh et al., 1996; Moulasha and Rama Rao, 1999).Table 4.5: Percentage distribution of women currently using contraceptivesclassified by their background characteristicsVariables Percentage Variables Percentage Variables PercentageAge*** Place of residence** Caste ***

Use of contraceptives differs with the standard of living of the women. InMalappuram district, women belonging to the low standard of living categoryare more users of family planning methods (71.6 percent) when compared tothose come under medium (54 percent) and high (54.8 percent) standards ofliving (χ 2 significance at 1% level). Similar trend is evident when the educationalbackground of the respondents is considered. More users of contraceptives arefound among lesser educated women and also the husbands when compared tothose with more years of schooling. The proportion of users of contraceptivemethods among primary, upper primary and high school and more educationare respectively 67.7 percent, 62.3 percent and 51.5 percent. The correspondingproportion with regard to education of husbands is 72.4 percent, 58.6 percent and48.5 percent respectively (χ 2 significance at 1% level).When the use of contraceptives by age at consummation of marriage of women isconsidered, women with age at consummation of marriage is greater than orequal to 18 years have an edge over those with age at consummation of marriagebelow 18 years (58 percents over 56.3 percent respectively). Increase in thenumber of users of contraceptive users is observed with increase in maritalduration as one expects (χ 2 significance at 1% level).As anticipated a positive relationship exists between number of children andcontraceptive use. When 50.3 percent of women with 3 or less children usecontraceptives, 78.9 percent of those with more than 3 children are users of FPmethods (χ 2 significance at 1% level).Visit of a health worker of a family planning worker and the subsequent advicereceived on family planning matters do not show much variation withcontraceptive use. Those users who were visited by a Family Planning or healthworker have only a slight edge over those not visited. Awareness about familyplanning methods especially all the modern methods available is essential toincrease the acceptance rate. Among the users of contraceptives itself, it is foundthat more than half the women are not aware of all the modern methods (χ 261

significance at 5% level). Knowledge about spacing methods is vital amongthose women who haven’t achieved their desired family size. Here 50.6 percentare unaware of the modern spacing methods of contraceptives.4.4 Determinants of contraceptive useAnalysis hitherto deals with as to how the use of contraceptives varies withwomen’s background socio economic and demographic characteristics. But thefactors that determine the use of contraceptive could be different in differentpopulations. Research so far shows socio economic variables and demographicvariables influencing contraceptive use vary in different groups. Among thesefactors, the effect of education on knowledge to use non-terminal method moreeffectively (Bumpass, 1987), role of religious affiliation on acceptance ofsterilization due to behaviour related to childbearing (Chacko, 1988;Goldscheider and Mosher, 1988; Reddy, 1996), monetary and time costs ofobtaining contraception (Lewis 1986; Janowitz and Bratt 1996), the social stigmaof using contraceptives in an unsupportive setting (Bongaarts and Bruce 1995;Nag 1984), lack of knowledge (Basu 1984; Chaudhury 2001) desire for morechildren (Kumar et al. 1999; Santhya 2004) etc are much highlighted factors thathave an influence the use of contraceptives. So to understand the determinantsof contraceptives use in Malappuram district, multivariate statistical techniquesare employed. Here logistic regression analysis is employed as the dependentvariable use of contraceptives is dichotomous. The dependent variable is codedas Nonusers = 0 and Users = 1. Those background variables that showedsignificant association with use of contraceptives in the two way classificationand associated χ 2 test of significance are included here as the dependentvariables. The following table gives the details regarding the variables includedin the regression analysis.62

Table 4.6: Variables included in the regression analysisVariables Categories Frequency ParametercodingReligion Others 214 .000Muslims 679 1.000Caste Others 121 .000OBC 772 1.000Education of Women

Table 4.7: Results of Logistic regression analysis showing the determinants ofcontraceptive use in MalappuramInitial ModelFinal ModelVariables B Exp β B Exp βReligionOthers (R)Muslims -1.471*** 0.230 -1.538*** 0.215CasteOthers (R)OBC -0.176 0.838 -- --Standard of Living 0.049 1.050 -- --Education of Women

Table 4.7 draws inference on the factors that determine the use of contraceptivesin Malappuram district. The initial model (significant at 1% level) shows the setof dependent variables entered in the model. The final model (also significant at1% level) shows necessarily the policy variables that have strong influence onwomen’s contraceptive use after eliminating the variables that fail to significantlyexplain the dependent variable. Regression results thus derived reveal thatreligion, number of children a woman has, awareness about all modern methodsof contraceptives and husband’s education significantly explains the use ornonuse of contraceptives in Malappuram district.Considering the influence of religion in Malappuram district, which is virtually aMuslim dominated area, it is seen that Muslims are almost 78 percent less likelyto use contraceptives than those women belonging to other religious groups(p

whose husbands have more years of schooling are seen to be significantly lesslikely to use contraceptives than those with lower educational background whichpossibly suggests the influence of customs and traditions in controllingcontraceptive use other than education in the Muslim dominated district. Yetanother possible reason could be the male dominated migration in Malappuramdistrict where migration rate is the highest in the state.Women tend to resort to permanent methods of contraceptives once theycomplete their desired fertility and as expected here too, contraceptive useincreases as women attain their third parity. Women with more than threechildren are almost four times more likely to use contraceptives than those with 3or less children. This finding is significant at p≤ .01. This is a much anticipatedresult as the mean number of children ever borne in the sample is 2.56.Knowledge about contraceptive devices, often obtained with exposure to massmedia is am important variables associated with contraceptive use rate. Studiesindicate that higher educated women have a better knowledge to use nonterminalmethod more effectively (Bumpass, 1987). In Malappuram, we find thatwomen who are aware of all modern methods of contraceptives are almost twicemore likely to use contraceptives than those women who are not well informed.66

Chapter VSummary and ConclusionsMalappuram district is considered to be the most backward district in Kerala andit figures in the list of backward districts in India according to the classification ofUnion Ministry of Health and Family Welfare in India. Based on the compositeindex developed on the basis of socio-economic and demographic indicators byRam and Shekhar (2006), this district is still placed at a very low positioncompared to the other districts of Kerala. The rank of Malappuram district withregard to the composite index is 180 out of a total of 591 districts when most ofthe other districts of the state are well placed. Malappuram district has been thefocus of attention ever since the 2001 Census showed that the district recordedthe biggest decline in the growth rate of population in Kerala. Though thegrowth rate is pretty high compared to other districts, it signifies a dramatic dropin the birth rate in Malappuram. This study was planned to elucidate thepossible aspects that explain the high fertility in the district. Lack of data at thegrass root level that often hamper micro level analysis prompted the estimationof fertility at the panchayat level. Generation of thematic maps based onestimated fertility levels as an application of Geographic Information System inDemographic analysis formed the second objective of the study. Besides these,attempt was also made to identify the determinants of fertility and prevalenceand determinants of contraceptive use among ever married women.Birth rate in Malappuram district at the Panchayat level is estimated usingCensus data adopting the most widely used method of estimation of fertility thatrequires minimum available data known as the reverse survival method of fertilityestimation is used. To study the determinants of fertility and determinants ofcontraceptive prevalence, the Reproductive and Child Health Survey Round II,67

Phase I data is used. Multiple Classification Analysis (MCA) is employed tostudy the nature and magnitude of association of different socio-economic anddemographic variables on children ever born among women in the district. Thedeterminants of contraceptive use is studied by employing Logistic RegressionTechnique.Birth rate in Malappuram district for the period 1997-2001 is 23.3 births per 1000population. Among the 100 panchayats as of 2001, the panchayat withmaximum birth rate is Pookkottur panchayat of Malappuram block in ErnadTaluk with a birth rate of 27.8 and the least in Perumpadappu panchayat of theblock of the same name in Ponnani taluk with a birth rate of 18.4. Clusteranalysis allowed easier comparison and it was found that only one panchayatstood out from the rest and forms an outlier. This outlier was Pookkotturpanchayat of Malappuram block in Ernad Taluk with a birth rate of 27.8. Whenthe panchayats were classified as those with birth rate below the district averageof 23.3 births per 1000 population and those above the district average, thepanchayats with birth rates above the district average were mainly concentratedin the Ernad and Tirurangadi taluks. Nilambur, Perinthalmanna and Tirurtaluks also had a few panchayats with higher birth rates. Ponnani taluk was anexception from the lot in the sense that all the panchayats had very low birth rateranging from 18.4 to 20.6. Tirur taluk was also better placed in this regard as 14panchayats have birth rate below the district average. 10 panchayats ofNilambur taluk, 7 of Perinthalmanna taluk, 5 panchayats of Ernad and 3 ofTirurangadi taluk had birth rate below 23.Thematic maps generated on the basis of the estimated fertility rates enabled toexplore the possible association of socio economic, and demographic factors onfertility. The inverse relationship between literacy and fertility could be provedto a certain extent in Malappuram district. Most of the low fertility panchayats68

had high literacy rate and some of the high fertility panchayats had low literacyrates. Ponnani taluk as a whole and some panchayats of Tirur taluk,Chungathara and Thenjipalam panchayat etc were examples of low fertilitypanchayats with high literacy rate. On the other hand, most of the panchayatsfrom Ernad and Nilambur taluk were cases of high fertility populations underconditions of low literacy. In Malappuram district only one panchayat,Kavannur of Ernad taluk, showed sex ratio favourable to males. Thoughassociation between sex ratio and fertility cannot be established, it could beinferred that in panchayats with low fertility, sex ratio was on the higher side(also greater than the state average). Panchayats with high birth rate on thecontrary showed low sex ratio.With regard to the association of Work Participation rate and fertility, birth ratewas generally high in panchayats with low work participation rate and viceverse though there were many exceptions to this observation. But when theassociation between the proportion of agricultural workers and fertility level andthat of proportion of cultivators and fertility were examined, a positiveassociation was discernible in both cases. In some of the panchayats with higherproportion of agricultural workers, birth rate was also high as in the case ofVazhikadavu, Thazhekkode, Pozhur, Pandikad etc. The panchayats with lowproportion of cultivators and low birth rate were mostly in Ponnani Taluk, andsome panchayats in Nilambur Taluk.Multiple Classification Analysis (MCA) was employed to understand theprobable factors that explain high fertility in Malappuram. The nature andmagnitude of association of different socio-economic and demographic variableson children ever born among women in the district were studied usingReproductive and Child Health Survey 2004 Round II data. When CEB wasclassified by age of women, more than one-third of the women in the prime69

eproductive age groups of 20-24 years, who were yet to complete their childbearing, already had 2 children and about 14 percent had 3 or more children.Similarly among women in the 25-29 year age group, more than two fifths of thewomen had 2 children and an almost equal proportion of women had 3 or morechildren. The estimated figures for mean age of mother at 2 nd and 3 rd order birthwere about 21.8 years and 24.4 years respectively.Classification of CEB by type of residence, religion and caste revealed that morewomen hailing from the rural areas, also Muslim women and also thosebelonging to the OBC had 3 or more CEB compared to their urban, other religionand other caste counterparts respectively. The influence of standard of living onfertility was visible in the present sample from Malappuram district. Amongwomen in the low standard of living category, two thirds of the women had 3 ormore children whereas, among those women in the high standard of livingcategory, less than half of the women only had 3 or more CEB.The direct effect of age at marriage on CEB was also evident here with theproportion of women having 3 or more children more among those women withage at marriage less than 18 years. With regard to marital duration, as expected,CEB increased as marital duration increased. Education of the respondent andalso that of their husband showed negative relationship with the number ofchildren ever born. Among illiterate women, more than three-fourths had 3 ormore children. Majority of the women in the sample had 0-9 years of schoolingand among them more than half had 3 or more children and among those with10 and more years of schooling, only a quarter fell in this category. Education ofhusband also showed similar influence on the number of CEB to women.Though the proportion of women visited by health worker was less in thepresent sample, its importance was highlighted. Less than half of the women70

who had been visited by health workers had on an average 3 or more children incontrast to those two-thirds of the women who had not been visited by HealthWorkers having 3 or more children.With regard to use of contraceptives and the number of CEB, among the 58percent of the women who reported to be currently using contraceptives, aquarter of them had 2 children, and more than two-thirds had 3 or morechildren. This is a much expected result as women of higher parity tend to adoptdifferent methods more. Awareness about modern contraceptive methodsespecially modern methods was found to increase contraceptive use rate.The Grand Mean of CEB, as inferred from the results of MCA, was 2.56. Themultiple R 2 was 0.297 when all the independent variables were included.However this value increased to 0.551 when the covariates were included. Thismeant that all the independent variables (religion, caste, standard of living,education of women and their husband, age at consummation of marriage,current use of contraceptives and unmet need for family planning) togetherexplained only 29.7 percent of the variation in the dependent variable CEBwhereas, the independent variables together with covariates explained 55.1percent of the variations in the dependent variable CEB.The multivariate analysis employed to learn the mechanism of association ofsocio economic and demographic factors on CEB among women in Malappuramdistrict gives an impression that religion and caste of women do explain somedifferentials in fertility levels. Besides, at the household level, the standard ofliving and at the social circle, education of women has some association onobserved fertility. Age at consummation of marriage also is also a predictorvariable. But use of contraceptives emerged as the best predictor variable inMalappuram.71

The MCA results showed that fertility of Muslim women was higher than thosewomen belonging to other religious groups mainly Hindus and Christians.Similarly women belonging to OBC category also had higher MCEB whencompared to other caste category. The effect of standard of living on fertility wasquite evident as women in the low standard of living category had on an average2.95 children compared to 2.38 children among those who enjoyed high standardof living. Education of women as expected showed the inverse relationship withfertility. In Malappuram, where, more than two-thirds of the women had age atconsummation of marriage before the attainment of legal age at marriage, theexpected positive relation of fertility with age at marriage was true. Truly so,MCEB among women whose age at consummation of marriage was less than 18years, computed after adjusting for independent variables and covariates, was2.63 compared to 2.42 among those women whose age at consummation ofmarriage was 18 years or more.With regard to use of contraceptives, the findings here suggested that differencein fertility levels between users and non users of contraceptives exist. In factcontraceptive use emerged as the most significant predictor variable affectingfertility in this particular model. The unadjusted MCEB for this category was1.91 among users as against 3.05 among nonusers. The Eta value was also highestfor this variable. Even after adjusting for independents and also independentsand covariates the category means remained the same and the Beta values alsodid not show much variation. The adjusted values showed that users of anycontraceptive method had on an average only 2.07 children ever borne incontrast to 2.93 among non users. This again highlighted the importance of useof contraceptives. The obstacles to contraceptive use often include lack ofknowledge about methods or knowledge about the source to obtain services, andconcern about the side effects of different methods. Findings suggested thatwomen with unmet need for contraceptives had higher fertility than those who72

do not. The MCEB among women who had unmet need for all methods was 2.98as against 2.45 among those women who did not have unmet need forcontraceptives.Given the strong influence of contraceptive use on fertility in Malappuramdistrict, the determinants of contraceptive use based on the RCH Survey RoundII data 2004 was also analysed. The couple protection rate in Kerala during theyear 2004 touched 72.1 percent. If the district wise variation is accounted for, thehighest value was seen in Thiruvananthapuram district (97.6 percent) andMalappuram recorded the lowest couple protection rate of 49.6 percent(Economic Review, 2005).Among the currently married women in the sample, 56.9 percent of the womenwere current users of family planning methods. Among the users, femalesterilization dominated. Users of IUD/CuT/Loop counted up to 4.5 percent,Condom/Nirodh to 4.3percent and Oral Pills were used by only 1.6 percent ofthe women. A quarter of the women in the sample were still users of traditionalmethods of withdrawal and safe period where the rate of risk of conception waspretty high.Unmet need for contraceptives speak of the access and availability ofcontraceptive methods. About one-fifths of the women in Malappuram districthad unmet need for contraceptives of which, 7 percent were for limiting methodsand 11.6 percent were for spacing methods.Women belonging to the older cohorts were more users of contraceptives thanthe younger ones in their prime reproductive age groups, a much anticipatedresult. Urban women, though less in number in the present sample, were seen tobe using contraceptives more than their rural counterparts. As regards religion,73

lesser proportion of Muslim women use contraceptives compared to women inother religions. Similarly women belonging to OBC category were lesser users offamily planning methods compared to those in the other caste category. Womenbelonging to the low standard of living category, lesser educated women, thosewomen with age at consummation of marriage greater than or equal to 18 yearswere more users of contraceptives though there was only slight variation.Regression analysis revealed that religion, number of children a woman had,awareness about all modern methods of contraceptives and husband’s educationsignificantly explained the use or nonuse of contraceptives in Malappuramdistrict. Considering the influence of religion in Malappuram district, which isvirtually a Muslim dominated area, Muslims were almost 78 percent less likely touse contraceptives than those women belonging to other religious groups(p

were almost twice more likely to use contraceptives than those women who werenot well informed.To conclude, it can be said that, fertility in Malappuram is well above the stateaverage and the estimated panchayat wise fertility which allows identification ofhigh and low fertility population in a much deeper way, shows that low fertilityand high fertility panchayats are scattered all over the district. The presence ofbetter performing panchayats (with low fertility) mostly in the Ponnani Talukthrows a note of optimism that the replication of achievements noted in thisTaluk is possible in the other panchayats too if concerted efforts are made withparticular emphasis on high fertility panchayats. The probable associationbetween fertility and the available socio-economic indicators at the panchayatlevel discernible from the application of GIS, a database system with specificcapabilities for spatially referenced data as well as a set of operations for workingwith the data, showed that literacy and proportion of workers employed inagriculture do explain the level of fertility partially. High birth rates inpanchayats with higher proportion of agricultural labourers and low literacyrates indicates that proper programmatic intervention in such districts caneventually help in bringing down the birth rate in the district as a whole.The observed strong association of contraceptive use on Children Ever Bornindicates that improved contraceptive use can necessarily pave way for muchlower levels of fertility. The necessity of increasing awareness about thedifferent contraceptive methods also emerges as a top priority as the studyfinding highlight that awareness is a significant predictor variable ofcontraceptive use. The study findings reiterate the fact that there is substantialinfluence of religion on contraceptive prevalence rate in Malappuram and socontinued efforts have to be made or even new strategies have to be designedthat can succeed in cutting through the cultural barriers associated with religion75

as Malappuram is a Muslim dominated district. Since fertility decline in generalkicked off at a good pace among the Muslims at a later stage compared to theHindus or other religions, the onset of fertility decline in Malappuram too beganwith a time lag compared to the other districts due to Muslim dominancy in thedistrict. If programmatic efforts are concentrated on the high fertility panchayatsit will not be too long to see fertility in Malappuram comparable to the rest of thelow fertility districts in Kerala.76

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