Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Aug 1;47(8):1449-1456.
doi: 10.2337/dc23-1507.

The Association Between Depressive Symptoms, Access to Diabetes Care, and Glycemic Control in Five Middle-Income Countries

Affiliations

The Association Between Depressive Symptoms, Access to Diabetes Care, and Glycemic Control in Five Middle-Income Countries

Lena Merkel et al. Diabetes Care. .

Abstract

Objective: The relationship between depression, diabetes, and access to diabetes care is established in high-income countries (HICs) but not in middle-income countries (MICs), where contexts and health systems differ and may impact this relationship. In this study, we investigate access to diabetes care for individuals with and without depressive symptoms in MICs.

Research design and methods: We analyzed pooled data from nationally representative household surveys across Brazil, Chile, China, Indonesia, and Mexico. Validated survey tools Center for Epidemiologic Studies Depression Scale Revised, Composite International Diagnostic Interview, Short Form, and Patient Health Questionnaire identified participants with depressive symptoms. Diabetes, defined per World Health Organization Package of Essential Noncommunicable Disease Interventions guidelines, included self-reported medication use and biochemical data. The primary focus was on tracking diabetes care progression through the stages of diagnosis, treatment, and glycemic control. Descriptive and multivariable logistic regression analyses, accounting for gender, age, education, and BMI, examined diabetes prevalence and care continuum progression.

Results: The pooled sample included 18,301 individuals aged 50 years and above; 3,309 (18.1%) had diabetes, and 3,934 (21.5%) exhibited depressive symptoms. Diabetes prevalence was insignificantly higher among those with depressive symptoms (28.9%) compared with those without (23.8%, P = 0.071). Co-occurrence of diabetes and depression was associated with increased odds of diabetes detection (odds ratio [OR] 1.398, P < 0.001) and treatment (OR 1.344, P < 0.001), but not with higher odds of glycemic control (OR 0.913, P = 0.377).

Conclusions: In MICs, individuals aged 50 years and older with diabetes and depression showed heightened diabetes identification and treatment probabilities, unlike patterns seen in HICs. This underscores the unique interplay of these conditions in different income settings.

PubMed Disclaimer

Conflict of interest statement

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Figures

None
Graphical abstract
Figure 1
Figure 1
Univariable analysis: diabetes care outcomes. Shown are the proportion of people with diabetes who progress through the diabetes care cascade for respondents with and without depressive symptoms. The first bars are set to 100% and thus represent the whole sample (n = 3,209) who have diabetes, of which 808 had depressive symptoms and 2,501 did not. Diagnosis was received by 417 with and 1,145 without depressive symptoms. Treatment was received by 366 with and 959 without depressive symptoms. Glycemic control was achieved by 127 with and 439 without depressive symptoms. Results are unadjusted for confounding variables and rescaled using survey weights.
Figure 2
Figure 2
Multivariable analysis: depressive symptoms and diabetes care outcomes. Shown are point estimates and 95% exact CIs for the explanatory variable depressive symptoms on the diabetes care outcomes, receipt of diagnosis, receipt of treatment, and achievement of glycemic control. Coefficients are expressed as ORs. The x-axis is log transformed.

References

    1. Davies JI, Reddiar SK, Hirschhorn LR, Ebert CI, Marcus M-E, Seiglie JA, et al. Association between country preparedness indicators and quality clinical care for cardiovascular disease risk factors in 44 lower- and middle-income countries: a multicountry analysis of survey data. PLoS Med 2020;17:e1003268. - PMC - PubMed
    1. Dagenais GR, Gerstein HC, Zhang X, McQueen M, Lear S, Lopez-Jaramillo P, et al. Variations in diabetes prevalence in low-, middle-, and high-income countries: results from the prospective urban and rural epidemiological study. Diabetes Care 2016;39:780–787 - PubMed
    1. Manne-Goehler J, Geldsetzer P, Agoudavi K, Andall-Brereton G, Aryal KK, Bicaba BW, et al. Health system performance for people with diabetes in 28 low- and middle-income countries: a cross-sectional study of nationally representative surveys. PLoS Med 2019;16:e1002751. - PMC - PubMed
    1. Flood D, Seiglie JA, Dunn M, Tschida S, Theilmann M, Marcus ME, et al. The state of diabetes treatment coverage in 55 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 680 102 adults. Lancet Healthy Longev 2021;2:e340–e351 - PMC - PubMed
    1. Seiglie JA, Marcus M-E, Ebert C, Prodromidis N, Geldsetzer P, Theilmann M, et al. Diabetes prevalence and its relationship with education, wealth, and BMI in 29 low- and middle-income countries. Diabetes Care 2020;43:767–775 - PMC - PubMed