Is rural food security primarily associated with smallholder agriculture or with commercial agriculture?: An approach to the case of Mexico using structural equation modeling

ABSTRACT Obesity is a condition of excessive fat accumulation in adipose tissue that occurs due to nutritional transitions in food consumption patterns by population that practices modern lifestyles, trend to higher consumption of energy-dense foods and low physical activity. Food consumption is the main cause of adult obesity 18+ years old. Based on UNICEF (1998) concept, food consumption is influenced by food security, including food access and food availability. The purpose of this study is to determine the obesity and food security modeling in West Java Province. This study used secondary data from Riskesdas 2013, SUSENAS 2013, and Daerah Dalam Angka2013-2014 from BPS. Unit analysis is 26 districts of West Java Province. The data were analyzed using Partial Least Square - Structural Equation Modeling (PLS-SEM). The results showed that ten percent increase in food availability could directly reduce 9.2 percent in food access, reduce 8.9 percent in food consumption as a result of food access changes, and reduce 0.4 percent of obesity as a result of food access and food consumption changes. Ten percent increase in food access could directly increase in 3.0 percent of food consumption, and increase 3.6 percent obesity as a result of food consumption changes. Ten percent increase in food consumption could increase 6.0 percent of obesity prevalence. Keywords: obesity, food security, partial least square structural equation modeling (PLS-SEM) ABSTRAK Obesitas merupakan kondisi akumulasi lemak berlebih pada jaringan adiposa yang secara langsung disebabkan oleh transisi gizi, yaitu perubahan pola makan oleh populasi yang telah mengadopsi gaya hidup modern, yaitu kecenderungan pada peningkatan konsumsi makanan padat energi dan rendahnya aktivitas fisik. Penyebab utama obesitas orang dewasa 18+ tahun berasal dari konsumsi pangan. Berdasarkan konsep UNICEF (1998), konsumsi pangan dipengaruhi oleh ketahanan pangan, termasuk akses pangan dan ketersediaan pangan. Penelitian ini bertujuan untuk menentukan pemodelan obesitas dan ketahanan pangan Provinsi Jawa Barat. Penelitian ini menggunakan data sekunder, yaitu Riskesdas 2013, SUSENAS 2013, dan Daerah Dalam Angka 2013-2014 kabupaten/kota Provinsi Jawa Barat. Unit analisis adalah 26 kabupaten/kota Provinsi Jawa Barat. Analisis menggunakan pendekatan Partial Least Square - Structural Equation Modeling (PLS-SEM). Hasil penelitian menunjukkan bahwa peningkatan 10 persen ketersediaan pangan dapat secara langsung menurunkan akses pangan sebesar 9,2 persen, menurunkan konsumsi pangan sebesar 8,9 persen sebagai akibat dari perubahan akses, serta menurunkan prevalensi obesitas sebesar 0,4 persen sebagai akibat perubahan akses dan konsumsi pangan. Peningkatan 10 persen akses pangan dapat secara langsung meningkatkan konsumsi pangan sebesar 3,0 persen, serta meningkatkan prevalensi obesitas sebesar 3,6 persen sebagai akibat dari perubahan konsumsi pangan. Peningkatan 10 persen konsumsi pangan dapat meningkatkan prevalensi obesitas sebesar 6,0 persen. [Penel Gizi Makan 2018, 41(2):89-100] Kata kunci: obesitas, ketahanan pangan, partial least squarestructural equation modeling (PLS-SEM)

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Food security in Africa: a cross-scale, empirical investigation using structural equation modeling

Environment Systems & Decisions ◽

10.1007/s10669-017-9652-7 ◽

2017 ◽

Vol 38 (1) ◽

pp. 6-22 ◽

Cited By ~ 3

Author(s):

Riva C. H. Denny ◽

Sandra T. Marquart-Pyatt ◽

Arika Ligmann-Zielinska ◽

Laura Schmitt Olabisi ◽

Louie Rivers ◽

...

Keyword(s):

Food Security ◽

Structural Equation Modeling ◽

Structural Equation ◽

Empirical Investigation ◽

Equation Modeling

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Home Food Safety Practice and Household Food Insecurity: A Structural Equation Modeling Approach

Iranian Journal of Public Health ◽

10.18502/ijph.v48i10.3495 ◽

2020 ◽

Author(s):

Fatemeh ESFARJANI ◽

Hedayat HOSSEINI ◽

Ramin KHAKSAR ◽

Roshanak ROUSTAEE ◽

Haleh ALIKHANIAN ◽

...

Keyword(s):

Food Security ◽

Structural Equation Modeling ◽

Food Safety ◽

Food Insecurity ◽

Structural Equation ◽

Equation Modeling ◽

Household Food Insecurity ◽

Safety Practice ◽

Household Food ◽

Home Food

Background: Food safety and food security are interrelated concepts with a profound impact on the quality of human life. The current study, for the first time, was set to identify associations between home food safety practice and household food insecurity a structural equation modeling approach. Methods: In this cross-sectional study, urban households were selected from among 10 health centers of five districts of Tehran, Iran (2015). The following questionnaires were completed: socioeconomic status (SES), food security and food safety. Structural Equation Modeling (SEM) was applied for predicting the relationships between SES, food insecurity, and food safety in households. Results: Food security was observed in 56% of households. Mild, moderate and severe food-insecure households were determined to be 29%, 12%, and 3%, respectively. In addition, the scores of home food safety practice in 37.5%, 33% and 29.5% of the households were classified as desirable, acceptable and weak, respectively. Low-educated mothers having husbands with low educational and occupational level had a weaker food safety practice compared to high-educated ones. Based on the SEM results, an inverse association between food safety practice and food insecurity score was observed (t= -2.89, ɣ= 0.16). Conclusion: Food insecurity and undesirable food safety practice were relatively prevalent among households. In addition, the economic and social factors could inversely affect both food insecurity and food safety practices.

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Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

Journal of Individual Differences ◽

10.1027/1614-0001/a000135 ◽

2014 ◽

Vol 35 (4) ◽

pp. 201-211 ◽

Cited By ~ 3

Author(s):

André Beauducel ◽

Anja Leue

Keyword(s):

Structural Equation Modeling ◽

Negative Correlation ◽

Structural Equation ◽

Error Score ◽

Classical Test Theory ◽

Test Theory ◽

Equation Modeling ◽

Eysenck Personality Questionnaire ◽

Personality Questionnaire ◽

True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

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The Measurement Invariance of the Short Dark Triad

Journal of Individual Differences ◽

10.1027/1614-0001/a000322 ◽

2020 ◽

Vol 41 (4) ◽

pp. 207-218

Author(s):

Mihaela Grigoraș ◽

Andreea Butucescu ◽

Amalia Miulescu ◽

Cristian Opariuc-Dan ◽

Dragoș Iliescu

Keyword(s):

Structural Equation Modeling ◽

Item Response ◽

Structural Equation ◽

Dark Triad ◽

Theory And Practice ◽

Equation Modeling ◽

Scale Level ◽

High Stake ◽

Differential Functioning ◽

Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

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Childhood Intelligence Predicts Adult Trait Openness

Journal of Individual Differences ◽

10.1027/1614-0001/a000194 ◽

2016 ◽

Vol 37 (2) ◽

pp. 105-111 ◽

Cited By ~ 6

Author(s):

Adrian Furnham ◽

Helen Cheng

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Social Background ◽

Study Data ◽

Equation Modeling ◽

Direct Effects ◽

Data Set ◽

National Child Development Study ◽

Nationally Representative ◽

The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

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Celebrity Worship Among University Students in Malaysia

European Psychologist ◽

10.1027/1016-9040/a000029 ◽

2011 ◽

Vol 16 (4) ◽

pp. 334-342 ◽

Cited By ~ 5

Author(s):

Viren Swami ◽

Tomas Chamorro-Premuzic ◽

Khairul Mastor ◽

Fatin Hazwani Siran ◽

Mohammad Mohsein Mohammad Said ◽

...

Keyword(s):

Factor Analysis ◽

Structural Equation Modeling ◽

Structural Equation ◽

Attitude Scale ◽

Equation Modeling ◽

Future Research ◽

The West ◽

Factor Solution ◽

Movie Stars ◽

Three Factor

The present study examined conceptual issues surrounding celebrity worship in a Malay-speaking population. In total, 512 Malay and 269 Chinese participants from Malaysia indicated who their favorite celebrity was and completed the Celebrity Attitude Scale (CAS) as well as a range of demographic items. Results showed that the majority of Malay and Chinese participants selected pop stars and movie stars as their favourite celebrities, mirroring findings in Western settings. In addition, exploratory factor analysis revealed a three-factor solution of the CAS that was consistent with previous studies conducted in the West. Structural equation modeling further revealed that participant’s age was negatively associated with celebrity worship and that self-rated attractiveness was positively associated with celebrity worship. Overall, the present results suggest that celebrity worship in Malaysia may be driven by market and media forces, and future research may well be guided by use of the CAS.

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Further Insights Into the German Version of the Multidimensional Assessment of Interoceptive Awareness (MAIA)

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000404 ◽

2019 ◽

Vol 35 (3) ◽

pp. 317-325 ◽

Cited By ~ 6

Author(s):

Dorota Reis

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Equation Modeling ◽

Interoceptive Awareness ◽

Multidimensional Assessment ◽

New Instrument ◽

Confirmatory Factor ◽

Complex Models ◽

Approximate Zero ◽

Bayesian Structural Equation Modeling

Abstract. Interoception is defined as an iterative process that refers to receiving, accessing, appraising, and responding to body sensations. Recently, following an extensive process of development, Mehling and colleagues (2012) proposed a new instrument, the Multidimensional Assessment of Interoceptive Awareness (MAIA), which captures these different aspects of interoception with eight subscales. The aim of this study was to reexamine the dimensionality of the MAIA by applying maximum likelihood confirmatory factor analysis (ML-CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). ML-CFA, ESEM, and BSEM were examined in a sample of 320 German adults. ML-CFA showed a poor fit to the data. ESEM yielded a better fit and contained numerous significant cross-loadings, of which one was substantial (≥ .30). The BSEM model with approximate zero informative priors yielded an excellent fit and confirmed the substantial cross-loading found in ESEM. The study demonstrates that ESEM and BSEM are flexible techniques that can be used to improve our understanding of multidimensional constructs. In addition, BSEM can be seen as less exploratory than ESEM and it might also be used to overcome potential limitations of ESEM with regard to more complex models relative to the sample size.

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Analyzing Observed Composite Differences Across Groups

Methodology ◽

10.1027/1614-2241/a000049 ◽

2013 ◽

Vol 9 (1) ◽

pp. 1-12 ◽

Cited By ~ 101

Author(s):

Holger Steinmetz

Keyword(s):

Monte Carlo ◽

Structural Equation Modeling ◽

Measurement Invariance ◽

Structural Equation ◽

Monte Carlo Study ◽

Equation Modeling ◽

Factor Loadings ◽

Latent Mean Differences ◽

Partial Invariance ◽

Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

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