Impact of rural-urban environment on metabolic profile and response to a 5-day high-fat diet

Tahapary, Dicky L.; Ruiter, Karin de; Kurniawan, Farid; Djuardi, Yenny; Wang, Yanan; Nurdin, Siti M. E.; Iskandar, Elisa; Minggu, Dominggus; Yunir, Em; Guigas, Bruno; Supali, Taniawati; Rensen, Patrick C.N.; Sartono, Erliyani; Soewondo, Pradana; Harbuwono, Dante Saksono; Smit, Johannes W. A.; Yazdanbakhsh, Maria

doi:10.1038/s41598-018-25092-6

Cited by 11 publications

(14 citation statements)

References 43 publications

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“…Fourth, it must be noted that the SUGARSPIN study population represents an Indonesian population living in rural areas of Indonesia, hence results from this present study may need to be confirmed in the urban Indonesian population. However, a previous study had observed that adiponectin concentrations were not different between urban and rural Indonesians, which may support the generalizability of our results to the greater Indonesian population [40]. Fifth, We included different age groups for the two populations (aged >18 in the Indonesian population, aged 45e65 in the Dutch population).…”

Section: Discussionsupporting

confidence: 70%

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The associations of leptin and adiponectin with the metabolic syndrome in an Indonesian and a Dutch population

Sigit

Trompet

Tahapary

et al. 2021

Nutrition, Metabolism and Cardiovascular Diseases

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Section: Discussionsupporting

confidence: 70%

“…The interand intra-assay coefficients of variance (CV) of leptin were 2.2% and 3.2%. While for adiponectin, the inter-and intraassay CV were 3.1% and 7.0%, respectively [40].…”

Section: Assessment Of Leptin and Adiponectin Concentrationsmentioning

confidence: 94%

The associations of leptin and adiponectin with the metabolic syndrome in an Indonesian and a Dutch population

Sigit

Trompet

Tahapary

et al. 2021

Nutrition, Metabolism and Cardiovascular Diseases

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“…The higher-level functional pathways related to carbohydrate, protein and lipid metabolism were also found to be significantly associated with the rural location compared to urban slum location. These differences could be attributed to migration from rural to urban settings which has been previously reported to impair metabolic pathways (62) and gut microbiome composition (63,64). Although, the gut microbiome has been shown to affect the metabolism of macronutrients with the help of enzymes such as of CAZymes, deaminases, lipases, and others maintaining the homeostasis of metabolic pathways (65), however, the causal factors contributing to this remain speculative.…”

Section: Discussionmentioning

confidence: 99%

Gut Microbial Profile Is Associated With Residential Settings and Not Nutritional Status in Adults in Karnataka, India

et al. 2021

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Undernutrition is a leading contributor to disease and disability in people of all ages. Several studies have reported significant association between nutritional status and gut microbiome composition but other factors such as demographic settings may also influence the adult microbiome. The relationship between undernourishment and gut microbiome in adults has not been described to date. In this study, we compared the gut microbiome in fecal samples of 48 individuals, from two demographic settings (rural and urban slum) in Karnataka, India using 16S rRNA sequencing. Nutritional status was assessed based on BMI, with a BMI of < 18.5 kg/m2 classified as undernourished, and a BMI in the range 18.5–25 kg/m2 as nourished. We analyzed 25 individuals from rural settings (12 undernourished and 13 nourished) and 23 individuals from urban slum settings (11 undernourished and 12 nourished). We found no significant difference in overall gut microbial diversity (Shannon and Unweighted UniFrac) between undernourished and nourished individuals in either geographical settings, however, microbial taxa at the phylum level (i.e., Firmicutes and Proteobacteria) and beta diversity (unweighted UniFrac) differed significantly between the rural and urban slum settings. By predicting microbial function from 16S data profiling we found significant differences in metabolic pathways present in the gut microbiota from people residing in different settings; specifically, those related to carbohydrate and lipid metabolism. The weighted sum of the KEGG Orthologs associated with carbohydrate metabolism (Spearman's correlation coefficient, ρ = −0.707, p < 0.001), lipid metabolism (Spearman's correlation coefficient, ρ = −0.330, p < 0.022) and biosynthesis of secondary metabolites (Spearman's correlation coefficient, ρ = −0.507, p < 0.001) were decreased in the urban slum group compared to the rural group. In conclusion, we report that the geographical location of residence is associated with differences in gut microbiome composition in adults. We found no significant differences in microbiome composition between nourished and undernourished adults from urban slum or rural settings in India.

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“…A small number of studies have evaluated the impact of urbanization on insulin resistance in varied locations across the globe. A higher prevalence of insulin resistance was identified in Floresian men (a specific ethnic group in Indonesia) that had moved to an urban center (Jakarta) compared to men than remained in the rural area [39]. Similarly, another study revealed statistically significant higher HOMA-IR in Ghanaian adults living in urban areas compared to rural areas [40].…”

Section: Discussionmentioning

confidence: 99%

Urban environment as an independent predictor of insulin resistance in a South Asian population

et al. 2019

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BackgroundDeveloping countries, such as India, are experiencing rapid urbanization, which may have a major impact on the environment: including worsening air and water quality, noise and the problems of waste disposal. We used health data from an ongoing cohort study based in southern India to examine the relationship between the urban environment and homeostasis model assessment of insulin resistance (HOMA-IR).MethodsWe utilized three metrics of urbanization: distance from urban center; population density in the India Census; and satellite-based land cover. Restricted to participants without diabetes (N = 6350); we built logistic regression models adjusted for traditional risk factors to test the association between urban environment and HOMA-IR.ResultsIn adjusted models, residing within 0–20 km of the urban center was associated with an odds ratio for HOMA-IR of 1.79 (95% CI 1.39, 2.29) for females and 2.30 (95% CI 1.64, 3.22) for males compared to residing in the furthest 61–80 km distance group. Similar statistically significant results were identified using the other metrics.ConclusionsWe identified associations between urban environment and HOMA-IR in a cohort of adults. These associations were robust using various metrics of urbanization and adjustment for individual predictors. Our results are of public health concern due to the global movement of large numbers of people from rural to urban areas and the already large burden of diabetes.Electronic supplementary materialThe online version of this article (10.1186/s12942-019-0169-9) contains supplementary material, which is available to authorized users.

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Impact of rural-urban environment on metabolic profile and response to a 5-day high-fat diet

Cited by 11 publications

References 43 publications

The associations of leptin and adiponectin with the metabolic syndrome in an Indonesian and a Dutch population

The associations of leptin and adiponectin with the metabolic syndrome in an Indonesian and a Dutch population

Gut Microbial Profile Is Associated With Residential Settings and Not Nutritional Status in Adults in Karnataka, India

Urban environment as an independent predictor of insulin resistance in a South Asian population

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