Dataset Information

Rural-Urban Differences in Diabetes Care and Control in 42 Low- and Middle-Income Countries: A Cross-sectional Study of Nationally Representative Individual-Level Data.

ABSTRACT:

Objective

Diabetes prevalence is increasing rapidly in rural areas of low- and middle-income countries (LMICs), but there are limited data on the performance of health systems in delivering equitable and effective care to rural populations. We therefore assessed rural-urban differences in diabetes care and control in LMICs.

Research design and methods

We pooled individual-level data from nationally representative health surveys in 42 countries. We used Poisson regression models to estimate age-adjusted differences in the proportion of individuals with diabetes in rural versus urban areas achieving performance measures for the diagnosis, treatment, and control of diabetes and associated cardiovascular risk factors. We examined differences across the pooled sample, by sex, and by country.

Results

The pooled sample from 42 countries included 840,110 individuals (35,404 with diabetes). Compared with urban populations with diabetes, rural populations had ∼15-30% lower relative risk of achieving performance measures for diabetes diagnosis and treatment. Rural populations with diagnosed diabetes had a 14% (95% CI 5-22%) lower relative risk of glycemic control, 6% (95% CI -5 to 16%) lower relative risk of blood pressure control, and 23% (95% CI 2-39%) lower relative risk of cholesterol control. Rural women with diabetes had lower achievement of performance measures relating to control than urban women, whereas among men, differences were small.

Conclusions

Rural populations with diabetes experience substantial inequities in the achievement of diabetes performance measures in LMICs. Programs and policies aiming to strengthen global diabetes care must consider the unique challenges experienced by rural populations.

SUBMITTER: Flood D

PROVIDER: S-EPMC9472489 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rural-Urban Differences in Diabetes Care and Control in 42 Low- and Middle-Income Countries: A Cross-sectional Study of Nationally Representative Individual-Level Data.

Flood David D Geldsetzer Pascal P Agoudavi Kokou K Aryal Krishna K KK Brant Luisa Campos Caldeira LCC Brian Garry G Dorobantu Maria M Farzadfar Farshad F Gheorghe-Fronea Oana O Gurung Mongal Singh MS Guwatudde David D Houehanou Corine C Jorgensen Jutta M Adelin JMA Kondal Dimple D Labadarios Demetre D Marcus Maja E ME Mayige Mary M Moghimi Mana M Norov Bolormaa B Perman Gastón G Quesnel-Crooks Sarah S Rashidi Mohammad-Mahdi MM Moghaddam Sahar Saeedi SS Seiglie Jacqueline A JA Bahendeka Silver K SK Steinbrook Eric E Theilmann Michaela M Ware Lisa J LJ Vollmer Sebastian S Atun Rifat R Davies Justine I JI Ali Mohammed K MK Rohloff Peter P Manne-Goehler Jennifer J

Diabetes care 20220901 9

<h4>Objective</h4>Diabetes prevalence is increasing rapidly in rural areas of low- and middle-income countries (LMICs), but there are limited data on the performance of health systems in delivering equitable and effective care to rural populations. We therefore assessed rural-urban differences in diabetes care and control in LMICs.<h4>Research design and methods</h4>We pooled individual-level data from nationally representative health surveys in 42 countries. We used Poisson regression models to ...[more]

PMID: 35771765

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Project description:BackgroundUrban living affects children's nutrition and growth, which are determinants of their survival, cognitive development, and lifelong health. Little is known about urban-rural differences in children's height and weight, and how these differences have changed over time. We aimed to investigate trends in children's height and weight in rural and urban settings in low-income and middle-income countries, and to assess changes in the urban-rural differentials in height and weight over time.MethodsWe used comprehensive population-based data and a Bayesian hierarchical mixture model to estimate trends in children's height-for-age and weight-for-age Z scores by rural and urban place of residence, and changes in urban-rural differentials in height and weight Z scores, for 141 low-income and middle-income countries between 1985 and 2011. We also estimated the contribution of changes in rural and urban height and weight, and that of urbanisation, to the regional trends in these outcomes.FindingsUrban children are taller and heavier than their rural counterparts in almost all low-income and middle-income countries. The urban-rural differential is largest in Andean and central Latin America (eg, Peru, Honduras, Bolivia, and Guatemala); in some African countries such as Niger, Burundi, and Burkina Faso; and in Vietnam and China. It is smallest in southern and tropical Latin America (eg, Chile and Brazil). Urban children in China, Chile, and Jamaica are the tallest in low-income and middle-income countries, and children in rural areas of Burundi, Guatemala, and Niger the shortest, with the tallest and shortest more than 10 cm apart at age 5 years. The heaviest children live in cities in Georgia, Chile, and China, and the most underweight in rural areas of Timor-Leste, India, Niger, and Bangladesh. Between 1985 and 2011, the urban advantage in height fell in southern and tropical Latin America and south Asia, but changed little or not at all in most other regions. The urban-rural weight differential also decreased in southern and tropical Latin America, but increased in east and southeast Asia and worldwide, because weight gain of urban children outpaced that of rural children.InterpretationFurther improvement of child nutrition will require improved access to a stable and affordable food supply and health care for both rural and urban children, and closing of the the urban-rural gap in nutritional status.FundingBill & Melinda Gates Foundation, Grand Challenges Canada, UK Medical Research Council.

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Dataset Information

Rural-Urban Differences in Diabetes Care and Control in 42 Low- and Middle-Income Countries: A Cross-sectional Study of Nationally Representative Individual-Level Data.

Objective

Research design and methods

Results

Conclusions

Publications

Rural-Urban Differences in Diabetes Care and Control in 42 Low- and Middle-Income Countries: A Cross-sectional Study of Nationally Representative Individual-Level Data.

Similar Datasets

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