Public Health of Indonesia
E-ISSN: 2477-1570 | P-ISSN: 2528-1542
Original Research Factors influencing the utilization of the Modern Family Planning (MFP) method under the National Health Insurance in Indonesia: An analysis of the 2017 IDHS Maretalinia1* .
Heni Rusmitasari2 .
Supriatin3 .
Lili Amaliah4 .
Ellyzabeth Sukmawati5 , and Linda Suwarni6 1 PhD Program in Demography.
Institute for Population and Social Research.
Mahidol University.
Thailand 2 Department of Public Health.
Faculty of Public Health.
Universitas Muhammadiyah Semarang.
Indonesia 3 Nursing Science Program.
Cirebon College of Health Sciences.
Cirebon.
Indonesia 4 Public Health Study Program.
Mahardika Institute of Health Technology.
Cirebon.
Indonesia 5 Department of Midwifery.
Serulingmas College of Health Science.
Cilacap.
Indonesia 6 Faculty of Health Science.
Universitas Muhammadiyah Pontianak.
Indonesia DOI: https://doi.
org/10.
36685/phi.
Received: 17 May 2023 | Revised: 7 June 2023 | Accepted: 15 June 2023 Corresponding author:
Maretalinia.
PhD (Candidat.
PhD Program in Demography.
Institute for Population and Social Research Mahidol University.
Nakhon Pathom, 73170 Thailand Email: mareta.
21@gmail.
Phone: 6282376690768 Copyright: A 2023 the Author.
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium provided the original work is properly cited.
Abstract Background: Indonesia recently implemented a National Health Insurance program while simultaneously grappling with the challenge of unmet family planning needs.
Objective: This study aimed to examine the correlation between health insurance ownership and the utilization of family planning methods among married/in-union women in Indonesia.
Methods: This study employed secondary data analysis using the 2017 Indonesian Demography and Health Survey (IDHS).
The analysis included a sample of 18,411 married/in-union women.
Univariate, bivariate (Chisquare tes.
, and multivariate .
inary logistic regressio.
analyses were conducted to examine the relationship between health insurance ownership and the utilization of family planning methods.
Results: The analysis revealed that a small proportion of individuals with health insurance utilized family planning services.
Several factors were found to be associated with the utilization of family planning services, including ownership of health insurance, women's age, family planning decision-maker, socioeconomic status .
s measured by being in the richest quintil.
, and higher education attainment.
Conclusion: The findings of this study provide important insights for policymakers and public health practitioners regarding the integration of national health insurance programs and family planning initiatives in Indonesia.
It is crucial to address the low utilization rate of family planning services among those with health Future research should focus on fostering collaboration among all stakeholders to promote comprehensive education on freely accessible contraceptive methods, aiming to bridge the gap between policy implementation and effective utilization of family planning services.
Keywords: modern family planning.
MFP.
national health insurance.
IDHS.
Indonesian Volume 9.
Issue 2.
April - June 2023 family planning is not the only concern of women but also husbands/ partners as well (Ibrahim, 2.
Background National health insurance is a right and responsibility of all citizens.
According to regulation number 19 in 2016, health insurance is a guarantee in the form of health protection for participants to obtain health maintenance and protection benefits in meeting basic health needs given to everyone who has paid the dues or the dues are paid by the government (Pemerintah Republik Indonesia, 2.
Primary health care is the health facility where family planning services can be provided (BKKBN, 2.
Family planning services can be delivered directly after delivery to prevent pregnancy, spacing the birth, and sterilization (BPJS Kesehatan, 2.
In the Indonesian context, those who live in urban areas tend to use family planning methods because of socio-demographic factors, including services, education, income, employment, age, parity, ethnicity, and religion (Seran et al.
, 2.
The incidence of unmet needs of family planning methods is still high, around 10.
6 percent, and is mostly influenced by the history of family planning usage (Nisak, 2.
The study using IDHS (Indonesian Demographic Health Surve.
found women aged > 45 years dominantly had family planning unmet needs (Sumiati et al.
, 2.
similar study related to unmet needs of family planning found contraception, maternal age, motherAos education, number of childrenAos ownership, history of child death, wealth index, province of residence, knowledge about contraceptive use, and ever used anything to delay getting pregnant were determine the unmet needs of contraceptive use (Hastuti et al.
, 2.
The specific study focused on the Papua region (Eastern Indonesi.
and found that the factors associated with low participation in family planning methods among young married women were household expenditure and age at first sexual intercourse (Rahmadani et al.
, 2.
More than 200 million women in developing countries cannot access family planning (Morgan & Wright, 2.
In developed countries, the family planning method that is mostly used are sterilization and LARCs (Long-acting reversible contraceptio.
(Kavanaugh & Jerman, 2.
Each method has different access and availability.
Family planning is crucial for advancing reproductive, maternal, and child health (Morgan & Wright, 2.
One woman can use more than one contraceptive method.
reported in the United States that 99 percent of women with sexually active use at least one method of family planning (Becker, 2.
WomenAos and child health is still a concern in developing countries (Tojiyeva.
et al.
, 2.
Regarding the linkage between ownership of health insurance and family planning usage, some interesting points can be observed regarding whether women under national health insurance can access free family planning.
According to the role of (BKKBN/Badan Kependudukan dan Keluarga Berencana Nasiona.
BKKBN had the responsibility to purchase family planning (FP) commodities in coordination with BPJS Kesehatan (National Health Insuranc.
(Teplitskaya et al.
, 2.
Services covered by primary healthcare facilities, particularly for modern family planning methods, were distinguished into capitation and fee-for-service.
For the capitation, there are family planning counseling, sexual and reproductive health services, and family planning commodities such as pills and condoms.
For fee-for-services, there are insertion and/or removal of IUD .
ntrauterine devic.
/implant, tubectomy/vasectomy (Teplitskaya et al.
, 2.
Limited studies examine whether those owned health insurances tend to Regarding some issues in the family, contraception is necessary for economic development, human rights issues, and womenAos health (Cole & Geist.
Women of reproductive age face many potential risks due to the biological process, including pregnancy and childbearing.
Women have the autonomy to plan when and how many children they want, which fundamentally may affect their health and social.
The ability of women to control their fertility is representative of womenAos empowerment toward their roles, rights, and status (Cole & Geist, 2.
Despite traditional methods, modern use is more interesting since it includes barrier and hormonal methods, emergency contraception, and sterilization, thus high promotion in terms of rationalization, science, and global focus (Cole & Geist, 2.
In most populous Muslim countries, women remain the focus who need justice and equal positions with men (Martynez, 2.
issue of patriarchy needs to manage well because Volume 9.
Issue 2.
April - June 2023 choose the capitation family planning method, which is free for devices and services.
This study aimed to examine the correlation between ownership of health insurance and the utilization of modern family planning methods in Indonesia.
Data Analysis The studyAos dependent variable was the MFP method, categorized as non-capitation .
for the method that free service in primary health care .
or those who had national health insuranc.
that consisted of condoms and pills, another one is capitation .
for the od that free of devices but need the service fee that consisted of injection.
IUD, implant, vasectomy, tubectomy .
or those who had national health insuranc.
The main independent variable is the ownership of national health insurance which is categorized as did not have any health insurance .
, under the national health insurance PBI (Penerima Bantuan Iuran/ Recipients of Dues Assistanc.
paid by the local government .
, under the national health insurance non-PBI which paid themselves .
and had other health insurance including from private provider .
Other variables included in the analysis were womenAos age, place of residence, educational level, wealth index, occupation.
MFP decision maker, and husband/partner aspects, including educational level and occupational status.
The data were analyzed using descriptive statistics.
Chi-square, and binary logistic regression using STATA 17, licensed by Institute for Population and Social Research.
Mahidol University.
Methods Study Design This study used a secondary data analysis of the 2017 IDHS.
The Demographic and Health Survey (DHS) is a global survey focusing on fertility, family planning, and maternal and child health.
The IDHS was implemented by Statistics Indonesia (BPS) in collaboration with the National Population and Family Planning Board (BKKBN) and the Ministry of Health (MoH) of Indonesia.
The Indonesian government funded the survey, which took place from 24 July to 30 September 2017.
The Intermediate Care Facilities (ICF) provides technical assistance through the DHS Program, funded by the United States Agency for International Development (USAID), and offers financial support and technical assistance for population and health surveys in countries worldwide (Ministry of Health Republic of Indonesia, 2.
Our study used IDHS, which was downloaded, cleaned, and processed in May 2023.
The IDHS has been done in 34 provinces in Indonesia, with 100% representative of the Indonesian population.
Ethical Considerations The IDHS 2017 obtained ethical clearance from the National Agency for Research and Health Development.
Ministry of Health.
Republic Indonesia.
The raw data is available on the website https://dhsprogram.
com/data/ and is free to download after registration and received approval.
Samples/Participants The 2017 IDHS used stratified cluster-random sampling to select the sample (Ministry of Health Republic of Indonesia, 2.
The sample frame used was the Master Sample of Census Blocks from the 2010 Population Census.
The samples covered 1,970 census blocks in urban and rural areas from 49,250 households.
Our study only focused on all women of reproductive-aged 15 to 49 years old with marital status, specifically married and living with a partner .
aving active sexual activit.
According to the dependent variable of this study, we only selected the women who used the modern family planning (MFP) method.
After the data cleaning, the final number of participants was 18,411.
Results Table 1 shows that the majority of the respondents used the modern family planning (MFP) method with non-capitation .
59%).
Most women reproductive age who used the MFP had no health insurance .
98%).
Regarding the womenAos age, their age was mostly distributed to age 30 to 39 years old.
Regarding the place of residence, the differences between urban and rural were almost equal, but those living in rural were a bit higher .
31%).
More than half graduated from secondary school .
14%) and worked at the survey time .
57%).
Comparing the proportion within the five indexes of wealth, the highest proportion was the poorest women .
37%).
Join decision between Instrument The instrument used by IDHS 2017 was the standardized questionnaire.
This current study retrieved the raw data from the DHS website without additional data collection.
Volume 9.
Issue 2.
April - June 2023 women and husband/partner was the most answered for MFP decision makers .
07%).
According to husband/partner aspects, more than half of them graduated from secondary school .
23%), and almost all of them were working at the time of the survey .
04%).
Table 1 The general characteristics of the respondents Variables .
= 18,.
Dependent variable Modern contraceptive use With non-capitation With capitation Variables of mother Ownership of health insurance Not have National health insurance (PBI) National health insurance .
on-PBI) Other insurance WomanAos age Place of residence Urban Rural Educational level Not education Primary Secondary Higher Working status Not working Working Wealth index Poorest Poorer Middle Richer Richest The family planning decision maker Mainly women Mainly husband/partner Join decision DonAot know Variables of husband/partner Husband/partnerAos educational level No education Primary Secondary Higher DonAot know Husband/partner working status Not working Working Frequency Percentage 14,469 3,942 16,013 1,504 1,633 2,821 3,767 4,164 3,551 2,193 8,964 9,447 6,181 9,802 2,181 7,076 11,335 4,118 3,919 3,595 3,543 3,236 6,402 1,264 10,682 6,062 9,985 2,077 18,234 Volume 9.
Issue 2.
April - June 2023 Table 2 displays Chi-square test results, revealing that some variables correlated using MFP, such as ownership of health insurance, womenAos age, educational level of women, working status, wealth index, family planning decision maker, and husband/partner educational level.
However, place of residence and husband/partner working status did not correlate with the MFP method.
Table 2 The bivariate analysis of each independent variable with the modern family planning (MFP) Variables MFP with non-capitation Frequency Percentage Variables of mother Ownership of health insurance Not have 12,253 National health insurance (PBI) 1,373 National health insurance .
on-PBI) Other insurance WomanAos age
1,375
2,347
3,010
3,208
2,671
1,616
Place of residence Urban
7,015
Rural
7,454
Educational Level Not education Primary 4,666 Secondary 7,739 Higher
1,874
Working status
Not working 5,628 Working 8,841 Wealth Index
Poorest
3,217
Poorer
3,083
Middle 2,816 Richer
2,727
Richest
2,626
The family planning decision maker
Mainly women
4,595
Mainly husband/partner 1,075 Join decision 8,752 DonAot know
Variables of husband/partner Husband/partnerAos educational level No school
Primary 4,586 Secondary 7,898 Higher
1,757
DonAot know Husband/partner working status Not working Working 14,331 Note: ***p-value <0.
001, **p-value <0.
01, *p-value <0.
MFP with capitation Frequency Percentage p-value 3,760 1,949 1,993 1,515 2,063 1,448 2,494 1,807 1,940 1,476 2,087 3,903 Volume 9.
Issue 2.
April - June 2023 Table 3 The woman and partner variables related to the modern family planning method Variables .
= 18,.
Model 1
95% CI
AOR
AOR
Model 2
95% CI
Variables of mother Ownership of health insurance Not have Ref Ref National health insurance (PBI) 30*** 24 Ae 0.
29***
25 Ae 3.
National health insurance .
on-PBI) 25*** 18 Ae 0.
25***
18 Ae 0.
Other insurance 16*** 09 Ae 0.
16***
09 Ae 0.
WomanAos age Ref Ref 79 Ae 1.
79 Ae 1.
90 Ae 1.
90 Ae 1.
12 Ae 2.
13 Ae 2.
91***
34 Ae 2.
92***
35 Ae 2.
10***
48 Ae 2.
11***
49 Ae 2.
27***
59 Ae 3.
28***
60 Ae 3.
Place of residence Urban Ref Ref Rural 87 Ae 1.
88 Ae 1.
Educational level Not school Ref Ref Primary 79 Ae 1.
82 Ae 1.
Secondary 74 Ae 1.
74 Ae 1.
Higher 51 Ae 1.
48 Ae 0.
Working status Not working Ref Ref Working 97 Ae 1.
97 Ae 1.
Wealth Index Poorest Ref Ref Poorer 81 Ae 1.
81 Ae 1.
Middle 82 Ae 1.
81 Ae 1.
Richer 89 Ae 1.
88 Ae 1.
Richest 74 Ae 0.
71 Ae 0.
The family planning decision maker Mainly women Ref Ref Mainly husband/partner 49*** 41 Ae 0.
48***
41 Ae 0.
Join decision 59*** 55 Ae 0.
59***
55 Ae 0.
DonAot know 17 Ae 0.
17 Ae 0.
Variables of husband/partner Husband/partnerAos educational level No school Ref Primary 89 Ae 1.
Secondary 83 Ae 1.
Higher 69 Ae 1.
DonAot know 33 Ae 3.
Husband/partner working status Not working Ref Working 70 Ae 1.
Note: ***p-value <0.
001, **p-value <0.
01, *p-value <0.
Model 1 (Log likelihood = -9121.
LR chi2.
= 880.
33, prob>chi2 = 0.
Pseudo R2 = 0.
Model 2 (Log likelihood = -9125.
LR chi2.
= 871.
89, prob>chi2 = 0.
Pseudo R2 = 0.
The binary logistic regression result in Table 3 was tested to examine the correlation between all independent variables, especially the ownership of health insurance and other control variables, which were distinguished into two models.
Model 1 is the full model consisting of mother and husband/partner Volume 9.
Issue 2.
April - June 2023 aspects, and Model 2 only consists of mother the capitation, all the devices and services were free, but fee-service means the devices are free, but the services need to pay.
This is an issue because the implementation of family planning services will be provided by health care under the investigation and evaluation from BPJS Kesehatan or Health Social Security Agency.
However, the family planning devices are provided by BKKBN or Population and Family Planning Affairs.
Local government involvement is also diverse because some provinces give free devices and services .
nsertion and removal proces.
, but others do not.
In this study, those with health insurance were less likely to choose the capitation method, meaning they used their own money for contraceptives even though they had health insurance.
In Model 1, it was found that those who are members of National Health Insurance (NHI) PBI (Penerima Bantuan Iuran/ Recipients of Dues Assistanc.
had a 70% probability to donAot using the MFP method with capitation compared to those who had no NHI after adjusted with other independent variables.
Furthermore, women who had NHI non-PBI increased 75% probability to donAot using the MFP, and women who had other insurance had an 84% The odds between Model 1 and Model 2 were almost similar.
In terms of the womenAos age, increasing womenAos age .
-34, 35-39, 40-44, and 45-.
is increasing the odds .
60, 1.
91, 2.
10, and 2.
27, respectivel.
of using MFP with capitation after adjusting to all independent variables comparing to women aged 15 to 19 years old.
The adjusted odds ratio for womenAos age variable between Model 1 and Model 2 seems According to the variable of the MFP decision maker, it was found husband/partner as a decision maker, join decision .
omen and husband/partne.
, and AudonAot knowAy was 0.
49, 0.
40 times less likely to use MFP with capitation comparing with women as the main decision maker after adjusted to all independent variables.
Between Model 1 and Model 2, there was no significant difference adjusted odd ratio.
Regarding womenAos age, older women tend to use the capitation method, mostly consisting of shortterm contraceptives.
It might be due to the simple process of short-term contraception because getting older will lead women to make everything simple and The family planning decision maker is a woman, and the husband/partner joins, so it was less likely to use the capitation family planning They tend to use non-capitation, which consists of long-term contraceptives.
The decision to choose non-capitation instead of capitation might be due to the effectiveness of the long-term method.
According to the two models constructed, the variables of the husband contributed to the models, but the impact is not that high.
Moreover, in Model 1, it was found that the richest women were 0.
84 less likely to use MFP with In Model 2, it was found that women who graduated from secondary school were 0.
67 times less likely to use MFP with capitation.
To decide the best model, it was not significantly different between Pseudo R2 in Model 1 and Model 2.
In detail.
Pseudo R2 was 0.
0460 and 0.
0456, which was not significantly different, so adding the variables of husband was not affect the correlation between ownership of health insurance and MFP method Previous studies reported that health insurance claims for the short-term contraceptive method were higher than for long-term contraceptives (Becker.
Similar findings were revealed in France that long-term contraceptives are rarely used compared to short-term ones (Agostini et al.
, 2.
It was reflected that the majority of owners of health insurance utilized the short-term contraceptive that capitation or, in other words, there is no fee needed to pay in primary health care.
Another study brought the community health insurance scheme .
ocal leve.
, which improved family planning services (Fakunle et al.
, 2.
The finding from the previous study was a bit different because the current research focused on national health insurance, but the results revealed the significant impact of health insurance in general on providing family planning Unfortunately, this study only focused on married/in-union women.
in Indonesia, family Discussion The study results found that the main predictors are ownership of the family planning method, family planning decision-makers, and womenAos age.
Not many studies focused on the correlation between health insurance and family planning method.
For Volume 9.
Issue 2.
April - June 2023 planning was targeted at married ones.
However, the study in the United States reported the low-cost or even free services of family planning for teenagers (Packham, 2.
One study in the United States also reported that 4 percent of the birth rate declined after conducted the contraceptive insurance mandates (Dills & Grecu, 2.
The usage of contraceptives was diverse for those who use national and private health insurance, and owners of national health insurance tend to use contraceptive services compared to those who use private (Kavanaugh et al.
, 2.
In the United States, in 2012, there was the Patient Protection and Affordable Care Act (ACA), one private health insurance covering the contraceptive device for free.
However, it was not effective because the insurance at the state level was mandated for contraceptives already (Mulligan, 2.
Supporting the previous studies, it was found that most of the long-term contraceptive method users have paid by themselves (Broecker et al.
, 2.
There are some differences in the implementation of family planning services in developed and developing countries.
an aging society, the biggest concern of the government is older people because adult of reproductive age is very independent, including accessing health and family planning services (Maretalinia & Suyitno, 2.
contribute to the development of collaborative programs that benefit public health as a whole.
Conclusion The utilization of the capitation family planning method among those who owned health insurance was found to be significantly low.
Despite having health insurance, women often opted for family planning methods that were not fully covered by their insurance, requiring them to pay out-of-pocket fees.
Several factors were found to be associated with the utilization of the capitation family planning method, including ownership of health insurance, women's age, the decision-maker for family planning, being the richest, and graduating from higher school.
gain a more comprehensive understanding, future studies should delve into the specific roles played by BPJS Kesehatan (Health Social Security Agenc.
and BKKN (Population and Family Planning Affair.
in promoting and facilitating access to the capitation family planning method.
By examining these roles in greater detail, researchers can identify potential barriers and opportunities for improvement in the utilization of this method, leading to more effective strategies for family planning and improved healthcare outcomes.
Declaration Conflicting Interest The authors declared no competing interest.
In general, the study findings shed light on the factors that influence the utilization of modern contraception methods in the context of national health insurance.
From a public health perspective, this research can provide recommendations on how to align national health insurance programs with family planning initiatives.
This alignment would enable individuals seeking modern contraceptives to easily access them through their national health Moreover, governments can actively participate in this For example, the government of Jakarta Capital Special Region has introduced an additional health insurance program called the "Kartu Jakarta Sehat" or "Healthy Jakarta Card" to support the national health insurance program.
Funding None.
Acknowledgment The authors acknowledge IDHS and the National Government for allowing us to use the data for this study.
Author Contribution M.
HR, and S obtained and analyzed the data and developed the topics.
LA.
ES, and LS contributed to the studyAos conceptualization and design.
All authors critically reviewed the manuscript and took part in the discussion All authors read and approved the final manuscript to be published.
Author Biography Maretalinia is a PhD candidate at the PhD Program in Demography.
Institute for Population and Social Research.
Mahidol University.
Thailand.
Heni Rusmitasari is a Lecturer at the Department of Public Health.
Faculty of Public Health.
Universitas Muhammadiyah Semarang.
Central Java.
Indonesia.
Supriatin is a Lecturer at the Nursing Science Program.
Cirebon College of Health Sciences.
Cirebon.
Indonesia.
Furthermore, this study has the potential to foster collaboration among stakeholders in the nation's public health efforts.
Various aspects of public health, including administration, health policy, and reproductive health, are addressed in this study.
addressing these aspects, the research can Volume 9.
Issue 2.
April - June 2023 Lili Amaliah is a Lecturer at the Public Health Study Program.
Mahardika Institute of Health Technology.
Cirebon.
Indonesia.
Ellyzabeth Sukmawati is a Lecturer at the Department of Midwifery.
Serulingmas College of Health Science.
Cilacap.
Indonesia.
Linda Suwarni is a Lecturer at the Faculty of Health Science.
Universitas Muhammadiyah Pontianak.
Indonesia.
Kavanaugh.
Douglas-Hall.
, & Finn.
Health insurance coverage and contraceptive use at the state level: Findings from the 2017 Behavioral Risk Factor Surveillance System.
Contraception: X, 2, https://doi.
org/10.
1016/j.
Kavanaugh.
, & Jerman.
Contraceptive method use in the United States: Trends and characteristics between 2008, 2012 and 2014.
Contraception, 97.
, 14-21.
https://doi.
org/10.
Maretalinia.
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Readiness of healthcare providers to face the aging society in Indonesia.
Philippine Journal of Health Research and Development, 25.
, 61-64.
Martynez.
An ethnographic study of domestic violence and divorce in Uzbekistan Master Thesis.
Lund.
Sweden: Sociology of Law Department.
Lund University.
Ministry of Health Republic of Indonesia.
Survei Demografi dan Kesehatan Indonesia 2017.
Jakarta:
Ministry of Health Republic of Indonesia.
Morgan.
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The role of health insurance in family planning.
https://w.
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Contraception use, abortions, and births: The effect of insurance mandates.
Demography, 52.
, 1195-1217.
https://doi.
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7/s13524-015-0412-3 Nisak.
Determinants of unmet needs in married women in Indonesia (Indonesian Dhs Analysis Jurnal.
Biometrika dan Kependudukan, 10.
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Family planning funding cuts and teen childbearing.
Journal of Health Economics, 55, https://doi.
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Pemerintah Republik Indonesia.
Undang-Undang Dasar Negara Republik Indonesia Nomor 19 Tahun https://peraturan.
id/Home/Details/3758 2/uu-no-19-tahun-2016 Rahmadani.
Fatiah.
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The dominant factors affecting the low participation of young women ever married in the family planning program (KB) in Papua Province .
7 IDHS data analysi.
Open Access Macedonian Journal of Medical Sciences, 10(E), 411-415.
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Seran.
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Prahastuti Sujoso.
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Pakaya, , & Adriyani.
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