Jurnal Gizi dan Dietetik Indonesia (Indonesian Journal of Nutrition and Dietetic.
Vol.
Issue 3, 2022: 87-99 Available online at: https://ejournal.
id/index.
php/IJND DOI: http://dx.
org/10.
21927/ijnd.
Gross domestic product and geographic area as social determinants of child stunting and severe stunting in Indonesia: A Multilevel analysis Tri Siswati1.
Lukman Waris3.
Bunga Astria Paramashanti4.
Hari Kusnanto5.
Joko Susilo2 1PUI-NOVAKESMAS.
Poltekkes Kemenkes Yogyakarta.
Jalan Tata Bumi No.
Gamping.
Sleman.
Daerah Istimewa Yogyakarta.
Indonesia, 55293 2Poltekkes Kemenkes Yogyakarta.
Jalan Tata Bumi No.
Gamping.
Sleman.
Daerah Istimewa Yogyakarta.
Indonesia, 55293 Department of Public Health.
Universitas Faletehan.
Jalan Palamunan No.
Kramatwatu.
Serang.
Banten.
Indonesia, 42161 4Department of Nutrition.
Faculty of Health Sciences.
Universitas Alma Ata.
Jalan Brawijaya No.
Kasihan.
Bantul.
Daerah Istimewa Yogyakarta.
Indonesia, 55183 5Faculty Medicine.
Public Health and Nursing.
Universitas Gadjah Mada.
Jalan Farmako.
Sekip Utara.
Depok.
Sleman.
Daerah Istimewa Yogyakarta.
Indonesia, 55281 *Correspondence: tri.
siswati@poltekkesjogja.
ABSTRAK
Latar Belakang: Stunting masih menjadi masalah kesehatan masyarakat di Indonesia.
Kesenjangan sosioekonomi dan geografis termasuk akar masalah stunting pada anak.
Tujuan: Penelitian ini bertujuan untuk menganalisis sosial determinan stunting dan severe stunting pada anak-anak di Indonesia.
Metode: Penelitian ini menganalisis data dari survei potong lintang Riset Kesehatan Dasar tahun 2013.
BPS, dan Kementrian Keuangan.
Sampel adalah 3,953 anak usia 6-23 bulan dan 10,215 anak usia 24-59 bulan.
Variabel dependen adalah prevalensi stunting dan severe Variabel independen meliputi faktor-faktor di tingkat sosial dengan mengendalikan faktor-faktor pada tingkat struktural dan biologis.
Data dianalisis menggunakan analisis multilevel dengan generalized linear mixed models (GLMM) untuk menguji random effects dan mixed effects pada variabel dependen terhadap stunting dan severe stunting balita.
Hasil: Gross Domestic Product (GDP) berkaitan dengan penurunan risiko stunting pada anak usia 6-23 bulan (Ar= 0.
95%CI: 0.
dan 24-59 bulan (Ar= 0.
95%CI: 0.
, serta penurunan risiko severe stunting pada usia 6-23 bulan (Ar= 0.
95%CI:
dan 24-59 bulan (Ar= 0.
95%CI: 0.
Rasio pajak hanya berkaitan signifikan dengan severe stunting pada usia 24-59 bulan.
(Ar= 0.
95%CI: 0.
Terdapat pula perbedaan geografis terkait stunting dan severe stunting.
Kesimpulan: Pertumbuhan ekonomi yang merata merupakan faktor yang penting untuk meningkatkan kesehatan dan kesejahteraan anak-anak stunting dan severe stunting di seluruh tatanan geografis di Indonesia.
KATA KUNCI: stunting.
produk domestik bruto.
area geografis.
determinan sosial.
88 Tri Siswati.
Lukman Waris.
Bunga Astria Paramashanti et all.
Vol 10.
Issue 3, 2022: 88-99
ABSTRACT
Background: Stunting remains a public health issue in Indonesia.
Socioeconomic and geographical disparities are among the root causes of stunting in children.
Objectives: This study aimed to analyze the social determinants of stunting and severe stunting children in Indonesia.
Methods: We analyzed data from cross-sectional surveys of IndonesiaAos National Basic Health Research in 2013, the Central Bureau of Statistics, and the Ministry of Finance.
Our samples were 3953 children aged 6-23 months and 10215 children aged 24-59 months.
Dependent variables were the prevalence of child stunting and severe stunting.
Independent variables covered factors at the social level while controlling structural and biological levelfactors.
Data were analyzed using a multilevel analysis using generalized linear mixed models (GLMM) for testing random effects and mixed effects of dependent variable on stunting and severe stunting children Results: Gross domestic product (GDP) was associated with the reduced risk of stunting among children aged 6-23 months (Ar= 0.
95%CI: 0.
and 24-59 months (Ar= 0.
95%CI: 0.
as well as with the decreased risk of severe stunting among 6-23 months (Ar= 0.
95%CI: 0.
and 24-59 months (Ar= 0.
95%CI: 0.
old children.
Tax ratio was a significant factor only for the severe stunting among 24-59 months old children (Ar= 0.
95%CI: 0.
There was also a geographical difference related to stunting and severe stunting.
Conclusions: Equitable economic growth is an essential factor to improve the health and welfare of stunting and severe stunting children across the geographical setting in Indonesia.
KEYWORD: stunting.
gross domestic product.
geographic area.
social determinants.
multilevel analysis Article info:
Article submitted on December 31, 2021
Articles revised on Jnauary 30, 2022
Articles received on February 4, 2022
INTRODUCTION
In Indonesia, stunting has the highest incidence of chronic malnutrition comparing other forms of malnutrition.
Stunting among children increased during 2010-2013 to as many as 1.
53% per year.
Meanwhile.
Strategic Development Goals have set a global stunting prevalence reduction of 40% by 2025 .
Based on these targets, it is necessary to decrease stunting by 1.
72% per year, so that stunting in Indonesia becomes 14% .
Stunting is a social problem, and the government has a responsibility to alleviate stunting problems in collaboration with many health and welfare programs and sectors .
Macroeconomic development is related to It may be the only way to alleviate malnutrition problems, especially in poor and developing regions .
, .
Accordingly, stunting is closely related to social indicators such as education, employment, income, and environment .
The disparity of stunting prevalence in Indonesia is vast and varied based on the geographical setting.
In Java-Bali, the prevalence of stunting children is the lowest while the areas in west Indonesia has the highest reported cases .
Stunting can impact all periods of human life, increasing the risk of infection .
, .
, impaired development .
, .
, poor school performance .
, .
, obesity in adults and metabolic syndrome .
, .
, less productivity and income .
, 7, .
, and increased economic burden .
Social determinants of health involve the circumstances of peopleAos lives that affect health status, especially for vulnerable groups, including young Thus, this study aimed to determine the social determinants for stunting and severe Gross domestic product and geographic area as social determinants of child stunting and 89 stunting among 6-23 and 24-59 months old Indonesian children.
MATERIALS AND METHODS
This research was cross-sectional using secondary data from IndonesiaAos Basic Health Research (Riskesda.
Central Bureau of Statistics .
Anti-corruption Agency .
, and Ministry of Finance .
The total population was 82,266 children aged 0-59 months across provinces during the Riskesdas survey in 2013.
The inclusion criteria of our study samples included: single birth and without chronic disease.
Children with any missing data and had height-forage Z-score below minus six and above six standard deviations (SD) were excluded from the Thus, we included a total of 14,168 children, consisting of 3,953 children aged below two years and 10,215 aged two years or above.
This research was approved by the Medical and Health Research Ethics Committee.
Faculty of Medicine.
Universitas Gadjah Mada.
Yogyakarta.
Indonesia KE/FK/0099/2017 dated January 27, 2017.
Dependent variables were stunting and severe stunting.
The height-for-age Z-score (HAZ) of the children was estimated using WHO Anthro Children were categorized as stunted if they had HAZ between -3 SD and <-2 SD whereas severely stunted children had HAZ <-3 SD .
Independent variables were social determinant variables such as gross domestic product (GDP), tax ratio.
Gini ratio, corruption perception index, poverty gap index, severity gap index, gender development index, women empowerment index, human development index, and geographic area.
Potential covariates that being controlled in this study were structural and biological factors.
Structural factors included parental education .
ow if completed junior high school or below, middle if completed senior high school and high if completed higher educatio.
, fatherAos occupation .
ot working.
non-formal if worked as entrepreneurs, farmers, fishermen or labours.
formal if worked as employees at government or private sector.
, household economic status .
ow if 1st and 2nd quintiles, middle if 3rd quintile, high if 4th and 5th quintile.
, number of household members (>5 or <.
, water access .
ufficient if the source of water was from tap water or protected spring water with good physical quality and could be accessed in less than ten meters away and less than five minutes, and adequate for 20L per person per day.
otherwise, not sufficien.
, sanitation .
ood if met the criteria as follows: a drain pipe/sewage and private toilet.
poor if one of the requirements was not me.
, cooking fuel .
raditional if used charcoal, briquettes, coconut shell, or firewood.
modern if used electricity, gas, or kerosen.
, and household iodine status .
ufficient if the results of household iodine test was blue colored.
otherwise, not sufficient or non.
Descriptive statistics was done to present the characteristics of the study samples.
Bivariable analyses were performed by multinomial logistic Adjusted relative risk ratio (A.
with 95% confidence interval (CI) were estimated, and those with p<0.
25 were entered into the multivariate analysis.
To obtain the most fitted model of the association between risk factors and stunting and severe stunting, we performed a multivariate multilevel analysis using generalized linear mixed models (GLMM).
We also conducted a manual backward elimination to retain factors associated with stunting and severe stunting at the level of significance of p<0.
The Ar with 95% CI were presented.
A likelihood ratio test was used to address the significant differences between the final model and the null model.
The collinearity test was applied to analyze the correlation between variables.
The analyses were done by STATA version 14.
2 (StataCorp.
College Station.
TX.
USA).
This study was ethically approved by te Medical and Health Research Ethics Committee (MHREC).
Faculty of Medicine.
Gadjah Mada University Ae Dr.
Sardjito General Hospital .
eference KE/FK/0099/EC/2.
RESULTS AND DISCUSSIONS
Stunting and severe stunting were more prevalent among 24-59 months children .
compared to 6-23 months .
97%).
Meanwhile, the mean and standard deviation (SD) of social risk factors were described as follows: GDP was 10A8.
81 billion.
Gini ratio was 0.
37A0.
perception corruption index (PCI) was 4.
86A0.
90 Tri Siswati.
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Vol 10.
Issue 3, 2022: 88-99 Figure 1.
The severity of childhood stunting among children aged 6-23 months in Indonesia Figure 2.
The severity of childhood stunting among children aged 24-59 months in Indonesia Gross domestic product and geographic area as social determinants of child stunting and 91 poverty gap index (PGI) was 1.
92A1.
02, severity gap index (SGI) was 0.
49A0.
36, gender development index (GDI) was 64.
62A3.
82, women empowerment index (WEI) 64.
85A 7.
Human development index 73.
29A2.
52 (HDI), tax ratio 9A5.
78, and health expenditure 3.
1A0.
The severity of stunting and severe stunting among children aged 6-23 months and 24-59 months in Indonesia varied across the geographic As seen in Figure 1 and Figure 2, the Middle part of Indonesia (Java.
Bali, and Kalimantan island.
had lower stunting and severe stunting prevalence than the Western and Eastern We also presented the childrenAos characteristics in Table 1.
The majority of our samples were born with average body weight and The breastfeeding proportion was only around 38%.
Approximately 33% of mothers and 27% of fathers of children in the two groups were short-statured.
More than half of the households had the highest quintile of economic status, whereas around half of the parents had a low educational level.
Table 1.
Characteristics of children aged 6-59 months Characteristic Sex Male Female Birth weight Low Normal Newborn length Short Normal Infection Yes, ever Never Exclusive breastfeeding Yes Vitamin A Supplementation Yes Immunization Incompleted Completed MotherAos height Short Normal FatherAos height Short (O 160 c.
Normal (>160 c.
Household iodine status None Insufficient Sufficient Number of household members O5 6-23 months .
= 3,.
24-59 months .
= 10,.
92 Tri Siswati.
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Issue 3, 2022: 88-99 Characteristic Number of children under-fives Ou2 FatherAos occupation Not working Non-formal Formal MotherAos occupation Not working Non-formal Formal FatherAos education Low Middle High MotherAos education Low Middle High Economic status Low Middle High Smoke exposure Yes Sanitation Poor Good Water access Insufficient Sufficient Cooking fuel Yes, traditional The results of the final model are discussed in Table 2.
The likelihood ratio N2 statistics were used to ensure each outcome variableAos dependence on the selected variables in the model.
For instance, among children aged 6-23 months, the model N2 statistics amounts to 95.
78 and is highly significant .
<0.
This indicates that the log 6-23 months .
= 3,.
24-59 months .
= 10,.
odds of stunting are related to the independent Similarly, this also applied to other outcome variables such as stunting at age 2459 months and severe stunting at age 6-23 months and 24-59 months.
Several factors were identified to be significantly associated with stunting and severe stunting.
Gross domestic product was associated with the Gross domestic product and geographic area as social determinants of child stunting andA 93 reduced risk of stunting among children aged 623 months (Ar= 0.
95%CI: 0.
and 24-59 months (Ar= 0.
95%CI: 0.
as well as with the decreased risk of severe stunting among 6-23 months (Ar= 95%CI: 0.
and 24-59 months (Ar= 0.
95%CI: 0.
old children.
Tax ratio was a significant factor only for the severe stunting among 24-59 months old children (Ar= 0.
95%CI: 0.
There was also a geographical difference related to stunting and severe stunting Table 2.
A multilevel analysis of social, structural, and biological risk factors for stunting and severe stunting among children aged 6-23 months and 24-59 months Variables Social
GDP
Tax Region Java-Bali, urban Java-Bali, rural Sumatera,urban Sumatera, rural Eastern Indonesia.
Eastern Indonesia.
Kalimantan, urban Kalimantan, rural Sulawesi, urban Sulawesi, rural Structural MotherAos education Low Middle High Economic status Low Middle High Number of household FatherAos occupation Not working Yes, non-formal Yes, formal 6-23 months Stunting Severe stunting Ar .
%CI) Ar .
%CI) 24-59 months Stunting Severe stunting Ar .
%CI) Ar .
%CI) 99.
1,32.
86-1,.
70-1,.
94 Tri Siswati.
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Issue 3, 2022: 88-99 Variables 6-23 months Stunting Severe stunting Ar .
%CI) Ar .
%CI) MotherAos occupation Not working Yes, non-formal Yes, formal Water access Insufficient Sufficient Biological Sex Male Female Birth weight Low Normal Birth length Short Normal MotherAos height Short 24-59 months Stunting Severe stunting Ar .
%CI) Ar .
%CI) 39.
,18-1.
Normal Constant (OR.
MOR) 097.
Standard error
Provincial (OR) Log likelihood
Model N2 statistics for LR test
0,021
12e-30 Ae 5.
<0.
56e-35 Ae 45 .
<0.
<0.
<0.
Normal FatherAos height Short OR: odds ratio.
AOR: adjusted odds ratio.
MOR: median odds ratio CI: confidence interval Our results showed that increasing 1 billion IDR in the GDP can reduce 1% of stunting and severe stunting.
A macro-economic approach was the prior choice to overcome stunting in development countries, as seen in Brazil .
, 36 poor countries .
Bangladesh and Nepal .
Senegal .
, and Indonesia using the 2010 Basic Health Research survey data from 2010 .
GDP can reduce the prevalence of malnutrition by improving the micro economy .
, .
, increasing capability to pay on goods related to nutritional and health status .
, improving access to health providers, food consumption, environment, housing, and education facilities .
Increasing of 1% tax ratio can reduce the prevalence of severe stunting of 24-59 months old children by 2%.
IndonesiaAos tax ratio achievement was below 20% of the target .
Tax changes involve a fiscal policy to achieve optimal economic growth, improving public health status and facilities such as schools, hospitals, roads, markets, hospital.
, reducing income gaps, improving the welfare of the population, sources of government expenditure, while addressing disparities in health in rural Gross domestic product and geographic area as social determinants of child stunting andA 95 and remotes areas .
Tax reform includes stabilization functions .
, while the implication is for improving health-related impact, health promotion while increasing prevention and curatives .
, and food price subsidies .
The geographical setting was an important issue contributing to IndonesiaAos stunting disparities, consisting of islands, land, water, mountains, urban, rural, and remote areas.
Geographical factors affect the environment, communication systems, transportation, public facilities, including education, health, and recreation .
, 32-.
Children living in Sumatra.
Kalimantan.
Eastern Indonesia, and rural areas generally have a higher risk of stunting/severe stunting.
Rural areas were also a risk factor for stunting, which is consistent with previous studies in Cambodia .
Nigeria .
, and Ghana .
The analysis of structural risk factors showed that parentsAo education, occupation, water access, and the number of family members influenced stunting and severe stunting (Table .
Education was a fundamental factor .
since education affects health through three ways: .
opportunities to gain good health knowledge, problem-solving skills and adapt to problems encountered, .
opportunities for better employment and income, and .
opportunities for an environment with good social support and social status .
Socio-economic disadvantages influence the genetic and biological system by long-term effects and neurobiological pathway complexity .
Studies demonstrated the consistency of the motherAos education with stunting children .
, .
Mothers play an important role in giving parenting and maintaining childrenAos health by providing sufficient food intake, caring, and Unfortunately, middle-educated adolescent girls tend to get married young and become pregnant, which is a strong predictor for small birth size .
, due to nutrition competition during pregnancy and growth .
Additionally, the occupation was closely related to income, social status .
, .
, and childrenAos malnutrition .
, 42, .
Other issues include an increased number of family members, which causes difficulties in distributing the motherAos attention and feeding practice to children .
The results also showed that clean water access was another risk factor for severe stunting children, while this was necessary to prevent infectious disease and lower stunting prevalence .
, .
The biology risk factors for stunting and severe stunting showed that low birth weight, length of birth, and parental stature were associated consistently, as seen in Senegal .
and Nigeria .
, and the results of a previous study in Indonesia .
, 48, .
Parental stature was found to be an intergeneration malnutrition problem .
, .
However, environmental factors can manipulate stunting children, including caring, parenting, breastfeeding, adequate nutrition, housing, clean water, sanitation, and economic improvement .
, .
Interventions for both specific and sensitive programs in the Aofirst thousand daysAo of early life proved to be an effective treatment .
and was found to provide almost 50% more benefit .
Results of this study further reinforce the findings that the success of the alleviation efforts for the widespread stunting problem largely depends on the governmentAos political commitment .
, health and welfare program involvement, and community support .
This is the first study in Indonesia determinants of stunting and severe stunting Our analysis involved representative data at the national level in Indonesia, which allowed us to determine the relationship across different predictorsAo levels.
Additionally, this studyAos multilevel mixed modeling enabled us to include the importance of social, structural, and Nevertheless, our conclusion was restricted by the cross-sectional surveyAos nature, which did not allow us to draw any causal-effect The data was also limited by the unavailability of nutrient intake and parenting 96 Tri Siswati.
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Issue 3, 2022: 88-99
CONCLUSIONS AND RECOMMENDATIONS
Gross geographical settings were the main risk factors for stunting and severe stunting children 6-23 months and 24-59 months old after controlling the structural and biological risk factors, while tax ratio was the main risk factor for severe stunting children 24-59 Improvement is especially needed in the equity of the GDP and tax ratio across the geographical area for the current stunting intervention programsAo success.
REFERENCES