... as cohabitation between parent(s), child and grandchild, or with siblings of the head of household for example. ... developed by Rele (1967) and Bogue and Palmore (1964). For instance ..... John Wiley and Sons, Chichester. Rees P. and P.
Application of the Own-Child method for estimating fertility of women by ethnic groups in the UK.
By Sylvie Dubuc OXPOP Working Paper no 47, June 2009
Abstract A number of socio-economic and cultural factors potentially influence fertility across and within countries, including ethnicity. However, apart from census data, little data is available, at least in the UK, to estimate fertility rates and thus fertility trends by ethnic groups between censuses. Previously, the Labour Force Survey (LFS) has been exploited to produce national total fertility rates (TFR) by ethnic groups up to 2001 using the reverse-survival Own Child Method (OCM). Here aspects of the OCM are refined to improve accuracy and tested against official statistics. The OCM is compared with results obtained using more straightforward techniques based on ChildWomen Ratios (CWR) using the same LFS data, and differences are discussed. The refined method is applied to produce recent fertility profiles by ethnic groups, including trends in the TFR and age specific fertility rates (ASFR), showing significant differences between groups.
Keywords Total Period Fertility, reverse survival, mortality retro-correction, family unit, household survey, Age-Specific-Fertility-Rate, Child-Women Ratio, Labour Force Survey, ethnicity.
1
Introduction
Fertility rates differ significantly across countries and within countries due to a variety of factors including ethnic and potentially religious affiliation. Providing accurate fertility estimates by ethnic groups is useful to further investigate underlying social and cultural causes of fertility. This, in turn, is of practical value for family planning policies. Other practical and political motivations include housing management and education (eg. schools requirements, language support). Furthermore, calculating fertility estimates by sub-groups, in reflecting specific demographic characteristics, may improve the whole population estimate by accounting for possible variation in its composition.
In the UK, a number of studies have shown fertility differentials by ethnic groups1, including published estimates up to 2001 (Rees 2007; Large et al. 2006; Coleman and Smith 2005). Fertility estimates by ethnic groups need to be updated. Conventional calculations of age specific fertility rates (ASFRs) are usually based on Birth Registration numbers divided by the Mid-year estimated number of women of fertility age, and by mother’s age (eq. 1). Total period fertility rates (TFR) are readily derived from ASFRs (eq. 2). Because birth registrations are not available by ethnic and religious groups, indirect methods have been used instead.
ASFR(x) = Number of births to women aged x / Number of women aged x
(eq. 1)
TFR = Sum of ASFR(x) * age-group of x (e.g. *1 if single year, *5 if five year group)
(eq. 2)
Census data currently constitutes the best source to derive fertility rates and trends by ethnic groups at regional and local geographical levels and have therefore been extensively used. For 2
instance using census data, “mothering ratios” based on the number of children aged 0 at the census divided by the number of women of fertility age (15 to 44 and by age) for each ethnic group have provided ASFRs, that have been used to produce local estimates (Large et al. 2006). The Child-Women Ratio (CWR) of main ethnic groups (based on children aged 0 to 4 to women aged 15 to 44 from census data) in conjunction with overall fertility rates by area, was used by Rees (2007) to produce regional fertility rates in the UK and later applied to produce local area estimates (Norman, 2008).
Some Hospital Episode Statistics on births by ethnic groups are available since the mid-1990s but ethnicity is not always recorded. They have been used to produce estimates in London (Klodawski 2003). Hospital records have improved recently with respect to ethnicity (in 2005, 89% of births in England and Wales recorded with an ethnicity) (Moser et al. 2008), promising a novel available data source for fertility estimates by ethnic groups at the national and sub-national levels. However, the data necessary to the denominator of the equation are currently not available. Other annual sources are available to derive estimates at national level, including the GHS (despite sample size limitations, see Coleman and Smith, 2005), the Labour Force Survey (LFS) and since 2004 the larger Annual Population Survey (APS) based on LFS data and boosted samples. The LFS is a household survey providing extensive information on household individuals including age, sex, ethnicity and religion. However, this source does not provide information on birth by age of the mother and, as for census data, indirect methods are needed to calculate fertility. The LFS together with the Own-Child Method (OCM) was first proposed in the UK by Berthoud (2001) in order to analyse teenage births to ethnic minority women, and was later applied by Coleman and Smith (2005) to produce national fertility rates from 1965 to 2001. A refined method of the latter, including deaths rates in the reverse survival method and a more appropriate mother-child 3
matching procedure, is described and applied here to produce inter-censuses annual estimates based on LFS data and fertility profiles by ethnic groups in the UK. The results obtained for all women in the UK are appraised against official estimates based on vital statistics. TFR by ethnic groups using the OCM are compared to estimates produced using CWR based on the same data source in order to discuss the merits of using various approaches. The potential of the refined LFS-OCM is illustrated by fertility rates calculated for the main ethnic groups in the UK, over the period 1987-2008.
Methodology
The Own Child Method to estimate ASFR and TFR by ethnic groups
OCM calculations are based on LFS data in the UK. The LFS surveys cover approximately 60,000 households each year and a record for each individual within households is available. The LFS is a quarterly annual survey and the third quarter (approximating mid year) of each year was used from 2001 to 2006. LFS data provides inter-censual data by ethnic groups based on the 2001 census definition. The OCM (presented below) uses LFS data only; therefore both the numerator and the denominator of the equation (eq. 1) are based on the same source, thus avoiding the risk of systematic bias when combining sources. Such bias would occur for example in the eventuality of underestimation of annual total number of women between censuses (estimations based on census or survey data) used against (nearly) exhaustive vital statistics. In this case, this would increase the fertility rates calculated. Despite the considerable sample size of the LFS, some limitations may arise when studying small groups (e.g. ethnic and religious minorities). However, the use of 4
surveys pooled across years offers a good solution to considerably increase the sample size, when using a reverse survival method of estimation.
The OCM (UN and NRC 1983; Cho et al. 1986) is a reverse survival technique for estimating 1 year ASFRs from a cross-sectional household survey. The approach makes use of the defined personal relationships within the LFS households to reconstruct child-mother relationships for previous years by computing child/mother ratios on their respective ages at the time of the survey (Figure 1). The required matching procedure has been automated (EasWesPop Program) and made available by East West Center (Honolulu, Hawaii). In using a relationship variable present in the LFS, the method seeks to ensure that females of childbearing age are not matched to their siblings or to their grandchildren. The program allows, within household, children 0-14 to be matched to women 15 to 60 years old in order to retro-construct the births to women of childbearing age, by age of the mother over 15 years prior to the survey. For instance, if in 2005 a child 14 years old was identified together with his/her 35 year old mother (Fig 1), it can be derived that the mother was 21 years old when her child was born in 1991. Because the Own Child method allows matching children to their mother within household, based on the relationship between household’s members, it presents the advantage, over a simple reversesurvival technique, to avoid or at least minimise the risk of selecting children not related to any woman in the survey.
The estimates produced using the OCM tends to have a systematic downward bias. For example, a women aged 35 in 2005 with a child aged 0, may have given birth when she was still 34, leading to a maximum of 1 year downward inaccuracy –and about 6 months on average- when estimating the age of the mother. This, however, is unlikely to greatly affect the analysis of fertility patterns 5
and the prediction of future trends that could be drawn. Retro-constructing births based on children who are older at the time of the survey brings the further advantage of minimising the well known and documented problem of undercounted infant in censuses and surveys. Another possible problem is that the method links children and mothers in the same household only. Because most of the children below the age of 15 stay with their mother in the event of their parents’ separation (Berthoud, 2001; Murphy and Berrington, 1993), the possible underestimation of fertility remains low. Furthermore, this potential underestimation may be partly compensated by a risk of overestimation of fertility in the cases where women are living with their stepchildren, both configurations being marginal however. Two other sources of possible underestimation of fertility concerning i) the previously applied matching procedure of individuals within households and ii) the lack of death rates have been recognised (Berthoud 2001). These aspects are considered in detail below.
21 born
mother child
1991
35 14
2005
time
Fig 1: Example of retro-construct of births to mothers for years prior to the survey.
OCM refinements
1. Using family unit instead of household The Own Child Method has been designed and previously used to match children to women within households, but more than one family may live within a household. The LFS provides for 6
each individual data to produce a household serial number and a variable for each person describing his/her relation to the head of household. Since 1992, a family unit codification and the relation to the head of family unit have been introduced. Here, this information is integrated (below) in the OCM approach and the differences in TFR estimates using family unit instead of household were tested.
Table 1 shows an example of a 5 member household (serial number 1114401001), comprising 2 family units. ‘RelHoH’ is the variable describing the relationship of each individual to the head of family unit (called relh06 since 2006 in the LFS) and ‘RelhFU’ is the variable describing the relationship of each individual to the head of family unit. One of 3 members whose head (relhfu = 1) is a male (sex=1) aged 31, his spouse (relhfu=2) is female (sex=2) aged 31 and his child (relhfu = 3) is a boy aged 2. The second family unit is made of a mother aged 35 and her daughter aged 7. Because the first family head happens to be the head of household, for family one there is no change in the codification when using the household to establish the relationship between its members, instead of using the family unit. In contrast, in this example, it makes a difference for the second family constituent of the household. Because the latter is not related to the first family (relhoh=12). In this case, the mother-daughter relationship is lost and therefore the program cannot match the daughter with her mother. For example, considering that the data was from the 2005 LFS, the mother of the second family unit was 28 (35-7 years) when her daughter was born in 1998. Therefore, for the year 1998, the mother is counted in the denominator of the ASFR equation (eq. 1), of the fertility rates of women aged 28. In contrast, the child is not recorded as a birth for the corresponding year (numerator of the equation eq.1). The program is sophisticated enough to recognise relationships between families within the household such as cohabitation between parent(s), child and grandchild, or with siblings of the head of household for example. 7
However, using the household unit rather than the family unit to match children to mothers has the potential to underestimate the number of children matched, especially within complex households, including unrelated, or remotely related, families.
Table 1: Extract of LFS data (fictive data sample) Serial H 1114401001 1114401001 1114401001 1114401001 1114401001
Serial FU 11144010011 11144010011 11144010011 11144010012 11144010012
RelHFU 1 2 3 1 3
RelHoH 1 2 3 12 12
Sex 1 2 1 2 2
Age 31 32 2 35 7
Serial H: household serial number; Serial FU: family unit serial number; RelHFU: relation to the head of family unit; RelHoH: relation to the head of household.
2. Correcting for mortality The Own-Child Method is a reverse-survival method which allows the derivation of the number of births (by age of the mother) in the past from the age of children in a particular survey year. Similarly, the number of women by age is retro-constructed. To enhance the accuracy of the OCM the number of births in the years prior to the survey were corrected for mortality occurring between birth and the age of the children at the time of the survey. Further retro-correction was applied to the number of women. The mortality by ethnic group is unknown. As a simplification, assuming the same mortality pattern for all groups2, the deaths rates of the UK population by sex and age (by 5 year age groups) between 1976 and 2006 provided by ONS (Table D9552) were used.
8
For children from 0 to 14 years old, the male-female mean of the annual death rate (death per 1000) was calculated. The average sex-ratio at birth between 1980 and 2005 is 105.2 boys per 100 girls and stable across time (Dubuc and Coleman, 2007)3. It remains very close to 105 in the population aged between 0 and 14 years old (ONS 2008) while the average sex-ratio for the population 0-14 years old is 105, fluctuating from 104.3 to 105.8 boys per 100 girls using single year ratios. Therefore a sex-ratio of 105 was used in the calculation of the mean mortality rates of infants and children by 5 years group of age. The mortality rate at birth and under 1 year old was cumulated to estimate the mortality rate at age 0.
CWR based approaches to estimate TFR by ethnic groups
TFR by ethnic groups can crudely be approximated by combining the general TFR based on vital statistics provided by the ONS (2008a) for the entire population (sum of all ethnic groups) multiplied by the ratio of child-women ratios of the ethnic group (eq 3).
TFR eth = TFR all x (CWReth/CWRall)
(eq.3)
Other methods have been proposed to derive TFRs from CWRs, including regression methods developed by Rele (1967) and Bogue and Palmore (1964). For instance, the below equation was proposed by Rele (eq. 4). In this case a linear regression can be applied between the CWR and TFR by using empirically derived parameters depending on life expectancy.
TFR = 2.05 GRR = 2.05 (-an+ bn CWR)
(eq.4)
9
Where GRR is the Gross Reproduction Rate, coefficients an and bn determine the linear relationship between TFR and GRR for a population with a level of mortality n (Hanenberg 1983).
The CWR is calculated as the number of children (0-4 years) to women (15-49 years), thus introducing an element of reverse survival analysis in referring to the period 0-4 years prior to the survey used. In contrast to the OCM, CWR assume constant fertility over time. Here, the CWR were applied to data from the 2004, 2005 and 2006 surveys and therefore provide an average fertility estimate covering the period 2000 to 2006. Both mode of calculation introduced above (eq 3 and eq 4) were tested.
Results
CWRs versus OCM
Examples of TFR calculated for selected ethnic groups using various methods are presented in Table 3. For most of the ethnic groups, the TFR obtained using one or the other method based on the CWRs are similar; the main dissimilarity being for the White British women group. In contrast, more variation is apparent when TFR derived from the CWRs calculations are compared with results from the OCM. If the estimates are produces for the same period of time, 2000-2006, some of the variation may be due to the use of a larger set of LFS data to produce OCM estimates (based on data from 2001 to 2006) compared to the CWR (using surveys 2004 to 2006) and therefore limits the conclusions that can be drawn from the comparison. However, the 10
comparative analysis remains instructive. The largest variation between methods relates to the mixed group and is very unlikely to be explained by the above limitations of the comparative exercise. The large difference in the estimates for the mixed group is easily explained by the CWRs constraint for children (numerator of the equation) to be of the same ethnic group than the women (denominator). Because the mixed population is generally young and rapidly growing in the UK, a large part of the mothers of children of mixed origin are not mixed themselves and therefore the numerator of the equation is largely overestimated when it comes to estimate the fertility of women of mixed origin. In contrast, the OCM allows for children of any ethnic group to be matched to mothers of a particular group, since matching is based on the relationship between family members. Therefore, the latter procedure reflects more accurately the fertility of women of mixed origin. In turn, this could explain, at least in part, the lower TFR recorded for the white groups, and in some extend for the Black Caribbean women. Indeed, the composition of mixed couples (Bradford 2006) and the distribution of mixed children by ethnic group of the mother from census 2001 data (ONS Commissioned table CO 432 in Coleman 2007) suggest that a large proportion of mixed children are of mothers belonging to these groups (White groups and secondarily Caribbean).
Methodological refinement to correct for fertility under-estimation
Household units and Family units have been used to match children to their assumed mothers, using the Own-Child Method. Fertility is slightly under-estimated when the children are matched to their assumed mother within household units, compared to the rates obtained using family units for the matching process. Comparison of TFRs for all women between 2000 and 2006 with both modes of calculations shows a variation of 1.6%. The difference introduced by the retro11
correction for mortality is small (0.37% higher), as corrections in the numerator and the denominator partly compensate (eq.2) and probably also because mortality for children and women of childbearing age is rare in the UK. Interestingly, underestimation varies across ethnic groups (table 2), fluctuating between 1% and 2.7%, with the Pakistani and Black African groups recording higher underestimations when family unit and retro-mortality corrections are not applied. This fluctuation is mainly due to the variation introduced by the use of family unit to match the children to their mother and may suggests higher frequency of more complex household for some groups (e.g. Pakistani and Black African).
In conclusion, the underestimation of fertility before refinement of the method using family unit and mortality retro-correction remains on average below 2% and always below 3%. Despite these relatively small variations, using the family unit matching and retro-correcting for mortality should increase the precision of the estimates and reflects the robustness of the method.
Table 2: TFR of main ethnic groups before and after refinement (using family unit and retro-mortality correction) Difference in the TFR (2000-2006)a Ethnic group % White British 1.35 White Other 1.70 Black Caribbean 1.51 Black African 2.76 Indian 1.09 Pakistani 2.67 Bangladeshi 1.90 Chinese 1.74 a
The difference recorded after refinement using family unit and retro-mortality correction compared to calculations based on household unit and without mortality correction
12
Table 3: Comparison of the average TFR 2000-2006 derived from the CWRs calculations and the Own Child method estimates. Ethnic groups White British White Other Indian Pakistani Black Caribbean Mixed
Estimates based on CWRs a TFR1* TFR2** 1.71 1.69 1.04 1.00 1.70 1.67 3.16 3.16 1.69 1.66 6.35 6.42
OCM b TFR 2000-2006 1.73 1.54 1.65 2.85 1.96 1.74
TFR1* = TFR eth = TFR all x (CWReth/CWRall) (eq 3) TFR2** = 2.05 GRR = 2.05 (-0.0309+3.4829 CWR) (eq. 4) a CWRs are based on counts from the LFS data 2004, 2005 and 2006 (3rd quarter) b OCM TFR is using data from 2000 to 2006 LFS and is based on 1 year ASFRs calculations.
Comparison with official statistics
The general trend for all women in the UK is in line with the available official data from the ONS based on vital statistics registration (Fig 2). The amplitude of the differences remains relatively small. Note that the data for the most recent years are more uncertain as they are based on smaller numbers. Indeed, the TFR value for 2006 is based on the sole 2006 survey data and 2005 TFR is based on the 2006 and 2005 data. In contrast the 2001 and previous years TFRs are derived from 6 survey’s data pooled together. The trend in ASFRs for all women in the UK calculated using the LFS is also conforming to published data from the ONS, observing (Fig 3) a drop in fertility for women below 30 and a rise of childbearing for older women. Further, the ONS data are solely based on births in the UK, when the LFS-OCM estimates will include births outside the UK to women who migrated to the UK since then. The later is more likely prior to the 2000s, when the proportion of births estimations based on older children present in the 2000 increase.
13
1.90 1.85 1.80
ONS LFS*
1.75 1.70
TFR 1.65
CI 95%
1.60 1990
1995
2000
2005
* 2 years average
Fig 2: TFR for all women 15-49 years old in the UK, 1990-2006
140
Births per 1,000 women
120 15-19 100
20-24 25-29
80
30-34 60
35-39 40-44
40
45-49 20 0 1986
1991
1996
2001
2006
1986-2006
Fig 3: Five years Age Specific Fertility rates for all women in the UK, 1986-2006
Fertility by main ethnic groups As expected, the fertility trend of the large majority ethnic group, the ‘White British’, fits well with the general trend (Fig 2) including a rise in the most recent years. For the main ethnic groups identified in the 2001 UK census (i.e. White British, 88,2% of the UK in 2001 census; Other White, 2.49%; Indian, 1.84%; Pakistani, 1.31%; Black Caribbean, 0.99%; Black African, 0.85%;
14
Bangladeshi, 0.5%; Chinese, 0.43%; Mixed, 1.18% for which the majority are children below 17 of age). The following groups, present in the 2001 census, are not analysed here: all Others (apart from ‘White Others’) including ‘Asian others’, ‘Black Others’ and ‘Others’ contribute 1% of the UK population and the White Irish, not stated in LFS data, 1.21%. The TFR by ethnic groups was calculated based on larger average periods as to allow for significantly meaningful general trends even for the small minority groups (Fig 4). Since the numbers are especially small for the women of mixed origin (about half of the mixed population was still below 16 years old in 2001) only the average period of 1987-2006 was produced for this group. Taken together, the average TFR of the
5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0
total1987-94 total1995-99
e es in Ch
hi de s la
ta n
i Ba ng
an di In
n ric a
Pa ki s
B. C
B. Af
th .O W
rit is .B W
ar ib be an
er
total2000-06
h
TFR
mixed groups for the whole period is relatively low (1.72), slightly below the UK average (1.78).
Fig 4: Fertility trendsa by main ethnic groups, 1987-2006. a
trend based on average periods (1987-1994, 1995-1999, 2000-2006)
Despite the rise recorded over the last 4 years, the TFR of the White British shows an overall decreasing trend over 1987-2006. The rise in the Black African and Caribbean TFR in the 90s is not continued in recent years (Fig 4). The most spectacular decreasing trends are those of the Bangladeshi and Pakistani groups, although decreasing from a very high level and still higher than
15
2.8 children per women (2000-2006) while the white British are below 1.8. The TFR of the Indian has fallen below the White British while the previously very low fertility of the White Other has been rising. Taken together, there is less variability in the estimates across groups in recent years compared to the 1990s.
The analysis of ASFRs for the larger groups reveals a postponement of childbearing marked for the women belonging to the White British and White Others groups (Fig 5). Late childbearing was already pronounced in the early 1990s for the ‘White Other’ women and have since been reinforced. Recently, an increase in the fertility rate of white other women in their early 20s is also noticeable. It may be hypothesised that this recent boost in young women fertility could be linked to a change in the composition of the group of White Others, with the rapid growth of immigrants from the EU new members. The fertility of Indian women in their 30s has also risen slightly while those in their 20s have experienced a clear fertility decrease. Noticeable also, is a rise of fertility of Black Caribbean women in their late 30s since the mid-1990s. In contrast, no sign of postponement appears for the Bangladeshi and Pakistani women (Fig 5). For these 2 groups of women the decline of the TFR is due to a decrease in the ASFRs at all ages and especially after 30 years of age for the Bangladeshi women. Teenage births rates to Bangladeshi women were remarkably high in the 1990s (Fig 5), as previously observed by Bertoud (2001). However, in the most recent period (2000-2006) the rate has become close to the white British group.
16
White British
White Other 140 Births per 1,000 women
Births per 1,000 women
140 120 100 80 60 40 20 0 1
-1 15
9
2
-2 20
4
39
-2 25
44
-3 30
59
-3 35
64
-4 40
120 100 80 60 40 20 0
79
-4 45
1 -1
15
9
2- 2
20
4
3-2
25
9
Indian
Births per 1,000 women
Births per 1,000 women
5-3
35
9
-4 6
40
4 45
9 -74
140
120 100 80 60 40 20 0
120 100 80 60 40 20 0
15
19
4 -2 20
25
29
4 -3 30
35
39
-4 40
4
9 -4 45
15
9 -1
20
- 24
25
-29
Births per 1,000 women
240 220 200 180 160 140 120 100 80 60 40 20 0
- 19
20
-24
25
- 29
30
-34
35
-39
30
-34
35
-39
40
- 44
45
9 -4
Bangladeshi
Pakistani
Births per 1,000 women
4
Caribbean
140
15
4-3
30
40
-44
45
-4
9
240 220 200 180 160 140 120 100 80 60 40 20 0
15
1987-1997 1998-2006
9 -1
20
4 -2
25
- 29
30
4 -3
35
-3
9
40
-44
45
9 -4 Age group of women
Fig 5: ASFRs of women by (selected) ethnic group, 1987-2006. The scale of the Y axis (number of births per 1,000 women) is similar for the White British, White Other, Indian and Caribbean women (up to 140) but different from the scale used for the Pakistani and Bangladeshi women (up to 240) to balance comparability and readability.
Discussion - Conclusion
The use of the Own Child Method and amalgamated LFS shows whole population TFR that are in good agreement with official data, evidence that the use of LFS-OCM is appropriate for inter censual ASFR and TFR estimates. OCM estimates are slightly underestimated using household
17
units compared to family units. The refinements of the method using mortality retro-correction and family unit have corrected for modest fertility under-estimation and reinforce the robustness of the method. Compared to more straightforward approximations of TFR by ethnic groups based on CWR, the OCM is sought probably more accurate, since i) TFR are directly derived from 1 year ASFR and do not rely on several data sources, ii) does not suffer from potential bias when comprising children aged 0-4, iii) is predicted to more realistically estimate TFR of the mixed group due to family unit matching that does not suffer matching mixed children to non-mixed parents and resulting in carry over errors in other ethnic groups. If the method is not suited to estimate TFR on local levels, facing the scarcity of data available by ethnic categories in between censuses, this technique offers a valuable relatively reliable mean of estimating fertility by ethnic groups at national level and their trend over time.
Generally, fertility differences between ethnic groups have reduced over time. Only the Chinese women with extremely low fertility in recent years tend to increase their difference. The decreasing and especially low fertility of Chinese women in recent years may result from a recent wave of students and highly skilled Chinese immigrants, belonging to social categories that are known for having especially low fertility rates. White Other and Indian groups are showing age patterns of childbearing similar to the majority ethnic group (postponement) and signs of delayed childbearing also characterise the Black Caribbean. In contrast, the strong fertility decline recorded by the Pakistani and Bangladeshi women over 1987-2006 results from lower fertility at all ages and is even more marked for older women. If fertility varies across ethnic groups, variations exist within groups depending on a number of factors including social and personal circumstances that still need being studied.
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Acknowledgements I am thankful to David Coleman for his collaboration. I am very grateful to Paul Norman for his helpful comments and suggestions. This work is supported by the Economic and Social Research Council (Grant RES-163-25-0049, UPTAP project).
References Cho, L.-J., R. D. Retherford, and M.K. Choe. 1986. The Own-Children Method of Fertility Estimation. Honolulu, University of Hawaii Press for the Population Institute, East-West Center. Berthoud, R. (2001) "Teenage births to ethnic minority women." Population Trends (104): 12 17. Bradford B, 2006, ‘Who are the 'Mixed' ethnic group?’. ONS publications, 39 p. Accessed 5 December 2007> Coleman D, 2007, Ethnic change in the populations of the developed world, Paper presented at the BSPS conference, St Andrew, September 2007 Coleman, D.A. and M. Smith. 2005. ‘The projection of ethnic minority populations: problems and data needs.’ OXPOP Working paper no. 13, Oxford, 63 p. Dubuc, S and D. Coleman. 2007. 'Recent changes in sex ratio at birth in England and Wales: evidence for sex selective abortion by India-born immigrant mothers' Population and Development Review 33, 2, pp 383-400. Hanenberg R. 1983. ‘Estimates of the total Fertility rate based on the Child-Women Ratio’, Asian and Pacific Census Forum.Volume 10, number 2, p5-10. Large P, K. Gosh and R. Fry. 2006. Population Estimates by Ethnic Group. Methodology Paper, Office for National statistics, 19 p. Moser K, Stanfield K. M. and Leon D.A. 2008 ‘Birthweight and gestational age by ethnic group, England and Wales 2005: introducing new data on births.’ Health Statistics Quarterly, no 39, pp22-31. Norman P. 2008 ‘Estimating fertility by ethnic group’, in Rees P, Norman P, Wohland P and Boden P Ethnic Group Population Trends and Projections for UK Local Areas, Presentation to 19
a Stakeholder Meeting, Thursday 18th December, 2008, GLA, City Hall, London , Accessed 19 January 2009. Klodawski, E. 2003. Fertility of Ethnic Groups in London. London, Greater London Authority. Murphy M. and A. Berrington. 1993. ‘Constructing parity progression ratios from household survey data.’ In Ni Bhrolchain M. (ed) New Perspectives on Fertility in Britain. HMSO (London 1993). ONS (2008a) ‘Table 2: Live births: TFR, GFR, Births within/outside marriage and percentage of births outside marriage, 1997-2000). . Accessed: 4 September 2008). ONS. 2008b. ‘Population by age, 2007’. United Kingdom, table in Focus on Gender, September 2008, ONS Centre for Demography. . Accessed: 25 October 2008. Rees P. 2007. ‘What happens when international migrants settle? Projections of ethnic groups in United Kingdom regions.’ Chapter 15 in Raymer J. and Willekens F. (ed.) International Migration in Europe: Data, Models and Estimates. John Wiley and Sons, Chichester. Rees P. and P. Wohland. 2008. ‘Estimates of ethnic mortality in the UK’, Working Paper 08/04. School of Geography, University of Leeds. 122 p. . Accessed: 12 January 2009. United Nations (Department of International Economic and Social Affairs. Population Division) and National Research Council (Committee on Population and Demography). 1983. Manual X: indirect techniques for demographic estimation. New York, United Nations. 304 p. (Population Studies, No. 81; ST/ESA/SER.A/81)
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1
Studies are based on the self-definition of the persons in the censuses of population in the UK.
2
Research on health inequality by ethnicity suggests that death rate patterns are likely to differ across ethnic groups.
Very recently, P. Rees and P. Wohland (2008) have proposed a method to estimate mortality by ethnic groups using illness ratios. In June 2008 the ONS has begun publishing new statistics on infant mortality by ethnicity in England and Wales showing differences across ethnic groups, with particularly much higher death rates to Pakistani and Black Caribbean infants. 3
Some variability in the sex-ratio of births to women based on their country of birth was also identified by Dubuc and
Coleman (2007) but can not be applied to ethnic groups without caution. Furthermore, because mortality rates for the whole population was adopted here, it was appropriate to apply average UK sex-ratio at birth.
21
