Scaling Up Family Planning to Reduce Maternal and Child Mortality ...
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The effects of family planning and other factors on fertility, abortion, miscarriage, and stillbirths in the Spectrum model
BMC Public Wellness volume 17, Article number:775 (2017) Cite this commodity
Abstruse
Background
The Lives Saved Tool (LiST) estimates the effects of maternal and child health interventions on mortality rates and the number of deaths. The family unit planning module in Spectrum interacts with LiST by providing estimates of the furnishings of scaling up family unit planning use on the number of live births, miscarriages, abortions, and stillbirths.
Methods
Nosotros apply the proximate determinants of fertility framework to estimate the furnishings of changes in contraceptive use, proportion married, postpartum insusceptibility, abortion and sterility on the full fertility rate. We extend this framework to guess the number of intended and unintended pregnancies and the resulting live births, abortions, stillbirths, and miscarriages.
Results
We apply the model to iv countries (Mali, Kenya, Indonesia, and Ukraine) to demonstrate possible trends with a range of family planning and fertility levels. In high-fertility countries, such as Mali, increases in contraceptive utilize will partially compensate for the increasing number of women of reproductive historic period to reduce the annual increases in pregnancies and births. Near unintended pregnancies occur to women defined as having unmet need for contraception. In low-fertility countries, increases in contraceptive use may reduce ballgame rates and low levels of unmet demand mean that most unintended pregnancies are due to method failure.
Conclusions
The family planning module in Spectrum provides a useful framework to incorporate changes in contraceptive practices and pregnancy outcomes in the LiST calculations of mortality rates and deaths.
Background
The Lives Saved Tool (Listing) model is concerned with rates of mortality for neonates, infants, children under 5 and mothers and the furnishings of wellness intervention scale-up on these rates. Listing likewise produces estimates of the full number of deaths and these are dependent on the number of alive births, abortions, and stillbirths. LiST is a part of the Spectrum software package, which has other modules that provide information to List. The HIV module (AIM) estimates the furnishings of HIV interventions (anti-retroviral therapy, cotrimoxazole, and programs to prevent mother-to-child transmission of HIV) on child deaths due to AIDS. The demographic project module (DemProj) estimates the number of live births, the number of children by unmarried age and the number of deaths to children under v [1]. The family unit planning module (FamPlan) estimates the furnishings of contraception and other factors on the number of pregnancies and pregnancy outcomes. The resulting fertility rates are used past DemProj to calculate live births, and the number of abortions and stillbirths are used directly by Listing to guess changes in the number of maternal and child deaths (Fig. one).
Construction of family planning effects in Spectrum
Several frameworks have been proposed for analyzing the factors that determine human fertility. Hobcraft and Little developed an approach that examines the private-level factors that affect individual fertility [2]. Wood developed a dynamic model of the proximate determinants of natural fertility (excluding contraception and induced abortion) that is also based on individual data [3].
An amass arroyo was proposed by Davis and Blake [4]. That approach recognized both indirect and directly determinants of fertility. Bongaarts adult these ideas into a useful framework for analyzing the proximate determinants of fertility [5,6,vii]. His arroyo explains the fertility-inhibiting effects of the fundamental direct determinants. The framework has been used for a variety of purposes, including (i) analyzing the contribution of changes in the proximate determinants to changes in the total fertility rate over time; (ii) comparison the differences in fertility betwixt two countries or regions on the basis of differences in the proximate determinants; and (three) estimating total abortion rates as a residuum later on the effects of all other proximate determinants have been removed.
Although there accept been some criticisms of Bongaarts' arroyo [3, 8] and suggested improvements to it [nine], his framework is widely used for analyzing fertility and fertility alter. It is the basis for the family planning calculations in Spectrum.
In this paper we showtime describe the methods used to chronicle pregnancy outcomes to measures of family planning need and utilize and and then apply to model to four countries to illustrate the results in different settings.
Methods
The proximate determinants of fertility framework developed past Bongaarts describes the factors that determine the observed total fertility rate (TFR): (i) marriage, (ii) contraception, (3) postpartum insusceptibility, (iv) induced abortion, (v) sterility, and (6) total fecundity. Definitions of these terms are provided below. The first five factors act to produce an observed TFR that is lower than total fecundity (the boilerplate number of births a woman would take if no factors were acting to inhibit fertility), as described in the following equation:
$$ {\mathrm{TFR}}_{\mathrm{t}}={\mathrm{Cm}}_{\mathrm{t}}\ \mathrm{x}\ {\mathrm{Ci}}_{\mathrm{t}}\ \mathrm{10}\ {\mathrm{Ca}}_{\mathrm{t}}\ \mathrm{x}\ {\mathrm{Cs}}_{\mathrm{t}}\ \mathrm{10}\ {\mathrm{Cc}}_{\mathrm{t}}\ \mathrm{x}\ \mathrm{TF} $$
where:
t = subscript denoting time
TFR = total fertility rate
Cm = marriage index
Ci = postpartum insusceptibility index
Ca = ballgame index
Cs = sterility index
Cc = contraception index
TF = total fecundity
Definitions of these terms are as follows:
Cm = proportion married or in marriage
The index of marriage adjusts fertility for the proportion of the fourth dimension from historic period xv to 49 that a woman is sexually active. The index is but the proportion of women of reproductive age who are married. Note that this implies that pregnancy does non occur to women outside of spousal relationship. In countries where there is a considerable amount of pregnancy outside of marriage this term can be redefined as 'in union' to include informal relationships. In some cases, it may be advisable to define this term as 'sexually active'. In that instance contraceptive prevalence needs to be amid sexually active women rather than the standard definition of prevalence amid married women.
$$ \mathrm{Ci}=20/\left(xviii.5,+,\kern0.025em ,\mathrm{PPI}\correct), where\ PPI\ is the median elapsing of postpartum insusceptibility in months $$
The index of postpartum insusceptibility adjusts fertility for the menstruation afterwards a birth during which a woman is protected from pregnancy either due to the fertility-inhibiting effects of breastfeeding or postpartum abstinence. It is calculated equally the ratio of the average birth interval in the absence of breastfeeding or postpartum abstinence (which Bongaarts estimated at 20 months) to the duration when these factors are taken into account, which is estimated as 18.5 months plus the median duration of postpartum insusceptibility.
$$ \mathrm{Cs}=\left(vii.63\hbox{--} 0.11\ \mathrm{x}\ \mathrm{s}\right)/vii.3, where\ s\ is the percentage of women anile\ 45- 49\ who\ have\ had\ no\ live births $$
The index of sterility is estimated from a regression equation that uses the prevalence of master sterility (the proportion of women who cannot get pregnant due to biological factors) to approximate the effects of primary and secondary sterility on fertility. Secondary sterility occurs when women of reproductive historic period who have had ane or more births can no longer excogitate. This index may be over-estimated in cases of voluntary childlessness.
Ca = TFR / (TFR + (0.iv ten (1 + CPR) 10 TAR), where TFR is the total fertility rate, CPR is the contraceptive prevalence rate, and TAR is the full abortion rate (the average number of abortions per adult female during her lifetime)
The index of abortion adjusts fertility for those pregnancies that are terminated by abortion. Each abortion reduces total fertility by less than one birth because information technology results in a shorter catamenia of gestation and more rapid render of fertility than a full term pregnancy. The net effect is estimated to be 0.iv births averted per abortion in the absence of contraceptive use. Higher rates of contraceptive utilise atomic number 82 to larger furnishings of abortion on fertility since the risk of conception is lower than without contraception. Since the index of ballgame is used to calculate the total fertility charge per unit this equation is commonly applied using TFR from the previous year.
$$ \mathrm{Cc}=1\hbox{--} i.08\ \mathrm{x}\ \mathrm{CPR}\ \mathrm{x}\ \mathrm{due east} $$
The index of contraception expresses the fertility inhibiting effects of contraception as a part of the proportion of women using contraception (CPR) and the average effectiveness of contraception given the method mix (e). The term 1.08 in the equation adjusts for that fact that some women who are sterilized may be post-menopausal, in which case the use of contraception has no fertility upshot. Average effectiveness is an boilerplate effectiveness of each method weighted by the proportion of users using that method. Standard method failure rates are based on analysis of data from developing countries by Cleland [10] and the The states by Trussel [11], as shown in Table one.
Total fecundity (TF) is the total number of live births women would have if none of these proximate determinants were acting to reduce her fertility; if she were continually married from age 15 to 49, did not breastfeed, did non experience primary or secondary sterility, did not have an abortion, and did non use family planning.
The value of total fecundity is unknown and appears to vary beyond countries due to factors not included in this framework (nutritional status, spousal separation, frequency of intercourse, etc.). Bongaarts suggested the range should be from well-nigh 13 to 18. Total fecundity can be estimated for any yr in which information on TFR and the other proximate determinants are available, usually from a national household survey. The proximate determinants equation can be re-bundled to guess total fecundity in that yr, as follows:
$$ \mathrm{TF}=\mathrm{TFR}/\left(\mathrm{Cm}\ \mathrm{x}\ \mathrm{Ci}\ \mathrm{ten}\ \mathrm{Cs}\ \mathrm{x}\ \mathrm{Ca}\ \mathrm{10}\ \mathrm{Cc}\correct) $$
Nosotros assume that total fecundity is constant over time. Thus, once the value of total fecundity is adamant, the proximate determinants equation tin can be used to calculate the effects of changes in any of the proximate determinants on the full fertility charge per unit. Using this framework, the family planning module in Spectrum calculates the TFR that results from future changes in contraceptive utilise, method mix, and the other proximate determinants.
In that location are some limitations to this framework. The major limitation is that it estimates the full fertility rate, which tin exist used to estimate alive births, just tells united states nix about pregnancies, pregnancy intentions, or pregnancy outcomes. In the FamPlan modue of Spectrum, we extend the framework to estimate the number of pregnancies from live births by adding miscarriages, stillbirths, and abortions.
Miscarriage (or spontaneous abortion) refers to natural pregnancy losses early in a pregnancy, unremarkably earlier xx weeks of pregnancy. The rates vary widely depending on how they are measured (from conception, at 4 weeks, at viii weeks, etc.). Past default, we use a miscarriage charge per unit of xiii% as estimated by Bongaarts and Potter [12].
Stillbirths are pregnancy losses later in pregnancy, usually as xx or 28 weeks of pregnancy. Country-specific estimates of stillbirth rates are bachelor and betoken a global average of near 19 stillbirths per g live births in 2009 [13].
Induced abortion refers to a procedure to end a pregnancy. The majority are done in the first viii weeks of pregnancy and almost all are done before the 13th week. Abortions in the 2d trimester (xiii weeks or later) or tertiary trimester are generally rare. Rates of induced ballgame are difficult to measure, in role because induced ballgame is illegal in many countries. Estimates of induced abortion rates are available [14] and suggest that worldwide about 25% of pregnancies end in induced abortion, with a variation from about xiii% in Middle Africa to 39% in the Caribbean area. An induced abortion is a response to an unwanted pregnancy. Some unintended pregnancies are unwanted only non all. Besides the rates of unintended pregnancies will change as contraceptive utilise changes. Therefore, it is preferable to express the induced abortion rate as a proportion of unintended pregnancies.
It is difficult to guess the proportion of pregnancies that are unwanted, partially because a woman may modify her mind once she becomes pregnant. Notwithstanding, we tin can estimate the number of unintended pregnancies equally those resulting from 2 sources: method failure and pregnancies occurring to women with an unmet need for contraception. Pregnancies due to method failure are calculated using the method failure rates given in Tabular array 1. The annual pregnancy rate among women with an unmet need for contraception is estimated to be 31% (inter-quartile plausibility range of 23–38%) [xv].
Unmet demand is divers as the proportion of fecund women who are not using contraception (mod or traditional) and are: (i) at hazard of condign pregnant only do not want to get pregnant in the adjacent 2 years or always or are unsure of their pregnancy intentions; (ii) pregnant with a mistimed or unwanted pregnancy; or (iii) postpartum amenorrheic for up to 2 years following a birth that was mistimed or unwanted [16]. Unmet need is measured in national household surveys and represents a rough estimate of the degree to which demand for contraceptive use exceeds actual use. Levels of unmet need vary every bit the use of contraception changes. The average pattern is shown in Fig. 2. Unmet demand is typically low when apply of family planning is very low. Demand tends to increase faster than utilise as CPR rises from zero to about twenty% leading to increased unmet need. And then contraceptive utilize rises faster than need and the proportion of women with unmet need declines.
Human relationship betwixt unmet need for contraception and contraceptive prevalence rate. Source: DHS information for 169 surveys from 71 countries [17]
With this approach, we can presume that the proportion of unintended pregnancies terminated past induced ballgame remains abiding over time, while the actual ballgame rate volition vary in accordance with changes in contraceptive use and unmet need. Note that this arroyo does non account for abortions that are done for the purposes of sexual practice choice.
Thus we accept the following equations to estimate the number of pregnancies and birth outcomes:
$$ \mathrm{P}=\mathrm{B}+\mathrm{A}+\mathrm{Chiliad}+\mathrm{South} $$
$$ \mathrm{A}=\mathrm{U}\ \upalpha $$
$$ \mathrm{U}=\mathrm{CU}\ \mathrm{x}\ \left(1\hbox{--} {\mathrm{due east}}_{\mathrm{t}}\correct)+\mathrm{United nations}\ \mathrm{ten}\ \uprho $$
$$ {\mathrm{Grand}}_{\mathrm{t}}=\left(\mathrm{B}+\mathrm{A}+\mathrm{S}\right)\ \mathrm{x}\ \upmu /\left(ane-\upmu \right) $$
$$ \mathrm{S}=\mathrm{B}/one thousand\ \mathrm{10}\ \upsigma $$
Where
P = number of pregnancies
B = number of live births
A = number of induced abortions
M = number of miscarriages
Southward = number of stillbirths
U = number of unintended pregnancies
CU = number of women using contraception
UN = number of women with unmet need for contraception
α = proportion of unintended pregnancies terminated by abortion
μ = proportion of pregnancies ending in miscarriage
σ = stillbirths per thousand live births
ρ = pregnancy rate for women with unmet need
These calculations are implemented in the family planning module in Spectrum and produce estimates of the total fertility rate, pregnancies, abortions, and stillbirths. The demographic module estimates the number of live births, and LiST uses all this data to gauge maternal and child mortality, stillbirths, and the effects of family planning on mortality. Note that since maternal mortality rates are different for alive births, stillbirths, and induced abortions, the changing distribution of pregnancy outcomes tin can alter the maternal mortality ratio as well equally the number of maternal deaths.
The effect of an increment in contraceptive use on number of pregnancies and pregnancy outcomes depends on the magnitude of scale-up. While the model can provide estimates for any increase in contraceptive apply, for planning purposes it is useful to utilise realistic rates of scale-upwards. Effigy iii shows the annual per centum-signal change in modern contraceptive prevalence for 257 inter-survey intervals for 93 countries with multiple Demographic and Health Surveys [17]. Each point represents the annual increase betwixt 2 sequent surveys. The average increase is about i percentage point per twelvemonth. Virtually 30% of the intervals have a growth rate to a higher place 2 points per year and only 6% have more than 3 points per year.
Distribution of the annual rate of change of modern contraceptive prevalence. Source: DHS data for 257 inter-survey intervals from 93 countries [17]
Results
In order to demonstrate the implications of the proximate determinates framework for a model such as the Spectrum software parcel, we will illustrate the range of effects of family unit planning on the number of pregnancies and pregnancy outcomes past examining four countries:
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Mali, as an case of a country with low apply of contraception and loftier fertility
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Kenya, as an example of a country with moderate utilise of contraception and medium fertility
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Indonesia, every bit an example of a country with loftier utilize of contraception and low fertility
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Ukraine, as an case of a country with moderate use of modernistic contraception only very low fertility due to the employ of traditional methods and abortion
The values of selected key indicators for these four countries are shown in Table two. Modern contraception includes sterilization, IUD, oral pills, injections, implants, condoms, and lactational amenorrhea. Traditional methods include withdrawal and periodic forbearance. Republic of mali has high fertility, low contraceptive use, high unmet demand, loftier proportion married, and long periods of postpartum insusceptibility. The long period of postpartum insusceptibility is due primarily extended breastfeeding; the median duration is 11.7 months. The lower levels of fertility in the other countries are associated with higher levels of contraceptive use and lower levels of unmet need, proportion married, and shorter duration of postpartum insusceptibility. As stated above, the loftier rate of induced ballgame is a major contributor to low fertility in Ukraine. These characteristics imply that in Republic of mali near i-3rd of pregnancies are unintended and most of those are due to unmet demand for contraception. By dissimilarity, in Ukraine, over 55% of pregnancies are unintended and most of those are due to method failure.
The effects of increases in contraception can exist illustrated by comparison 2 scenarios: commencement, assuming that contraceptive prevalence remains abiding, and 2nd, assuming that contraceptive prevalence increases past two points a twelvemonth in Republic of mali and Kenya and by ane indicate per year in Republic of indonesia and Ukraine, for a period of ten years. This latter scenario results in an increase in contraceptive prevalence from 10% to 30% in Republic of mali, from 42% to 62% in Kenya, from 62% to 72% in Indonesia, and from 67% to 77% in Ukraine. The furnishings of these increases on the pregnancies, births, abortions, and stillbirths can be seen in Fig. 4. Due to loftier rates of population growth in Mali and Kenya, the numbers of pregnancies and other outcomes would increase from 2015 to 2025 if contraceptive apply were to remain constant. With an increase in contraceptive use, pregnancies and live births would remain roughly constant in Mali but fall in the other 3 countries. The number of abortions would fall in all 4 countries.
Change in the number of pregnancies, births, abortions, and stillbirths over 10 years under constant or increasing contraceptive use scenarios
With constant utilise of contraception, the number of children under the historic period of v would increment by 33% from 2015 to 2025 in Republic of mali and by 27% percent in Kenya. The increase would be only 1% in Republic of indonesia, and Ukraine would experience a 19% decline because of its low fertility. With an increment in contraceptive use, the number of children nether five would increase by merely 8% in Mali and would decrease in Republic of kenya, Indonesia, and Ukraine past 14%, 21%, and 29%, respectively. These changes volition be reflected in the number of maternal and kid deaths estimated in LiST, fifty-fifty if mortality rates remain constant.
Discussion
Changes in the employ of contraception can accept important furnishings on maternal and child survival. An increment in contraceptive use leads to a reduction in the number of births which, all other things existence equal, means fewer maternal deaths, fewer stillbirths, and fewer children exposed to the risk of mortality. An increase in contraceptive use may as well affect the number of abortions, which affects maternal bloodshed. Changes in other proximate determinants – peculiarly marriage rates, abortion, and breastfeeding practices – can too take important effects on fertility.
The arroyo used in the Spectrum software parcel allows the effects of family unit planning and the other proximate determinants to exist included in LiST calculations in a consistent framework that links contraceptive use, fertility desires, abortion practices, and demographic processes to the maternal and child bloodshed calculations in LiST.
There are several limitations to this approach. The proximate determinants concept represents a useful framework to capture the primary effects of interest, merely it does non fully explain all the factors affecting fertility. The large variation in estimated levels of total fecundity probably reflect variations in other characteristics that affect fertility merely are non included in the framework and may be unmeasured. Dissimilar Listing, the family planning module does not simulate the effects of interventions designed to increase contraceptive use (such as postpartum family unit planning, social marketing, or community-based distributions programs) or the introduction of new methods, only instead requires the user to enter assumptions almost future changes in contraceptive employ. Nosotros are working to include these dynamics in future versions. Estimates of abortion and unmet need are subject to error and, therefore, estimates of the proportion of unintended pregnancies terminated by abortion are uncertain. We presume that these proportions remain constant with time just that may not be the instance when medical options or the legal environment modify.
Change in rates of contraceptive use are associated with changes in the distribution of births by key take a chance factors (short birth intervals, loftier parity, and maternal age below 18 or in a higher place 35) that are associated with elevated child mortality rates. We accept examined these relationships previously in society to include them in the model, but research and then far has plant merely weak causal effects [22,23,24].
The Sustainable Development Goals [25] call for improvements in many aspects of health, including family unit planning as well every bit maternal and kid survival. The Spectrum software package provides a system to examine these effects jointly, in order to capture the synergies that can be important to estimating time to come trends in child survival.
Conclusion
The number of child deaths in any population at any time results from a large number of factors that determine the number of births, the risks to which children are exposed and the wellness services they receive. The LiST model focuses on causes of expiry and the impact of interventions. The FamPlan and DemProj modules in Spectrum provide LiST with the number of live births each year as well every bit the number of stillbirths and abortions by considering the influences of contraceptive utilize, marriage and breastfeeding patterns and abortion rates. This link provides analysts and planners with a comprehensive picture of the factors that decide the number of child deaths.
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Acknowledgements
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Funding
Funding for the development of the FamPlan and DemProj modules in Spectrum was provided by USAID under sub-contract to Palladium through a series of contracts and cooperative agreements, including Health Policy Plus and Wellness Policy Project. The funders had no role in the design, collection, assay or interpretation of results for this article.
The publication costs for all supplement articles were funded past a grant from the Bill & Melinda Gates Foundation (JHU Grant 115,621, Award Number OPP1084423 for the "Evolution and Utilize of the Lives Saved Tool (List)").
Availability of information and materials
The Spectrum software including the DemProj, FamPlan and Listing modules tin can exist downloaded free of charge at: http://www.avenirhealth.org/software-spectrum.php. The database with complete demographic, family planning and kid wellness indicators for most countries in the world can also be downloaded from the aforementioned site.
Most this supplement
This article has been published as function of BMC Public Wellness Book 17 Supplement four, 2017: The Lives Saved Tool in 2017: Updates, Applications, and Future Directions. The full contents of the supplement are available online at https://bmcpublichealth.biomedcentral.com/articles/supplements/volume-17-supplement-4.
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JS developed the DemProj module in Spectrum, JS and BW developed the FamPlan module, BW developed the List module. JS performed the country analysis. JS and BW drafted the manuscript and approved the concluding version.
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Stover, J., Winfrey, W. The effects of family planning and other factors on fertility, abortion, miscarriage, and stillbirths in the Spectrum model. BMC Public Wellness 17, 775 (2017). https://doi.org/x.1186/s12889-017-4740-7
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DOI : https://doi.org/10.1186/s12889-017-4740-seven
Keywords
- Spectrum
- Avenir health
- Lives saved tool
- Family unit planning
Source: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-017-4740-7
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