National and regional trends in the prevalence of type 2 diabetes and associated risk factors among Korean adults, 2009–2021

Disproportionate impact of COVID-19 on socioeconomic and behavioral variables may have impacted the prevalence of diabetes. We utilized nationwide long-term serial study from the 2009 to 2021 Korea Community Health Survey (KCHS). We explored national and regional prevalence and trends of diabetes according to the socioeconomic and behavioral factors before and during the pandemic. Also, we interpreted which groups became more vulnerable to the prevalence of diagnosed diabetes during the pandemic. A total of 2,971,349 adults aged (19 to 39, 40 to 59, and ≥ 60 years) were included in the analysis. The prevalence of diagnosed diabetes increased slowly during the pandemic (11.6% [95% CI 11.5–11.7] in 2020 and 12.4% [95% CI 12.3–12.6] in 2021), compared to the pre-pandemic era (7.9% [95% CI 7.8–7.9] in 2009–2011 and 11.3% [95% CI 11.3–11.4] in 2018–2019). Also, women, low-income group, low-educational group, and infrequent walking group showed less prevalence of diagnosed diabetes than the others. The diabetic population increased slowly than expected during the pandemic. The pandemic seems to contribute to an unanticipated increase in under-diagnosis of diabetes among the already minority. This study may suggest reinforcing access to healthcare services among the minority during the pandemic.


Dependent variable
The survey period was the dependent variable.We separated the whole survey period into six-time segments; 2009 to 2011, 2012 to 2014, 2015 to 2017, 2018 to 2019, 2020, and 2021.Considering that the first COVID-19 case in South Korea was reported on January 20, 2020, 2020 was perceived as the early pandemic period and 2021 as the late pandemic period 9 .

Independent variable
The prevalence of diabetes is the independent variable.Participants were asked to self-report "Have you ever been diagnosed with diabetes by a doctor?", and were given binary response options for these questions, specifically "yes" or "no" 7 .
The variable of occupation was categorized into the following three groups: white (managers, professionals, and clerks), blue (service, sales, agricultural, forestry, fishery, craft, machine operating, elementary workers, and armed forces), and inoccupation (students and housewives), in accordance with to the Korean Standard Classification of Occupations 12 .BMI was calculated based on self-reported height and body weight.The participants were divided into four categories (underweight [< 18.5 kg/m 2 ], normal [18.5 to 23 kg/m 2 ], overweight [23 to 25 kg/m 2 ], and obese [≥ 25 kg/m 2 ]) according to the Asia-Pacific criteria of the Western Pacific Regional Office 2000 from the World Health Organization 13 .Basic livelihood security recipients defined as those received by the guarantee of a minimum standard of living and self-reliance for the poor and supported low-income households.

Statistical analysis
In order to examine the estimates of national prevalence, we performed a weighted complex sampling analysis 14,15 .We used the weighted linear regression models to assess the trend of diabetes rates over the past 13 years, targeting the period amidst the outbreak of COVID-19.Then, a difference of β (β diff ) was analyzed to explore the trend changes from 2009-2019 to 2019-2021 (before and during the pandemic).Also, we derived the weighted odds ratio (ORs) and 95% confidence interval (CI) from the weighted logistic regression models (2018-2019 to 2020-2021).Sex, education background, region of residence, BMI, income, smoking, alcohol drinking and walking were perceived as covariates in all the linear regression and logistic regression models 16 .BMI was reclassified into two categories: 'under and normal' and 'over and obese' .The frequency of walking variable was re-categorized into three groups (< 1, 1 to 4, and ≥ 5 times/week).Lastly, we obtained the ratio of ORs to estimate the interaction term of each risk factor 17 .We calculated the ratio of ORs for each category using the OR values obtained before and during the pandemic.This ratio allows us to interpret which groups became more vulnerable to the prevalence of diagnosed diabetes during the pandemic 18 .
All the statistical analyses were conducted with R software (version 4.2.2;R Foundation, Vienna, Austria) and Python software (version 3.9.13;Python Software Foundation, Wilmington, Delaware, USA).Testing was two-sided and p-values < 0.05 were considered statistically significant.

Results
The general characteristics of the participants were given in Table 1.Among the 2,971,349 valid participants, there were 1,344,538 (45.3%) men and 1,626,811 (54.7%) women.Also, 295,463 (9.9%) responded that they were diagnosed with diabetes.
To strengthen the hypothesis, we derived the ratio of OR of the prevalence of diagnosed diabetes before and during the pandemic and demonstrated in Fig. 1 and Table 3. Comparing the pre-pandemic and pandemic periods, men had a higher odds ratio of 8.4% (OR, 1.084; 95% CI 1.064 to 1.104) during the pandemic, while women had a lower increase in their odds ratio of 4.7% (OR, 1.047; 95% CI 1.028 to 1.066) then increase of men.To further clarify this evidence, we calculated the ratio of odds ratios, and indeed we found that that the prevalence of diabetes increased more significantly among men than women (ratio of OR, 1.035; 95% CI 1.009 to 1.062).In addition, high level of education (ratio of OR, 0.935; 95% CI 0.903 to 0.968), high income (ratio of OR, 0.921; 95% CI 0.885 to 0.959), and frequent walking (ratio of OR, 0.915; 95% CI 0.887 to 0.944) groups showed a higher prevalence of diagnosed diabetes during the pandemic compared with other groups.
Figures 2, 3 and 4 indicate regional prevalence of diagnosed diabetes.All rural regions show considerably higher prevalence of diabetes than urban regions.Nevertheless, the prevalence of all regions is presented the tendency of positive slope.

Key findings
To the best of our knowledge, this is the first large-scale study describing national and regional 13-year trends of the prevalence of type 2 diabetes in South Korea.We aimed to explore the trend difference in the diabetic population amidst the outbreak of COVID-19 and the factors associated with the prevalence.The findings of the study highlight that the diabetic population increased from 7.9% in 2009 to 2011 to 12.4% in 2021.The degree of increase in the number of people with diabetes has been slowed down during the pandemic.Furthermore, the prevalence of diagnosed diabetes differed substantially across socioeconomic subgroups during the pandemic, compared to the pre-pandemic era.During the pandemic women, those from low household income, low educational achievement and infrequent walking habits groups may have been underdiagnosed with type 2 diabetes due to disproportionate impact of COVID-19.

Comparison with previous studies
The results of this study align with previous studies; an increased prevalence of diabetes was observed due to a lack of access to medical care and preventive medicine in the pandemic era 6,19 .However, since they only analyzed the short-term trend of diabetes prevalence, they did not identify that during the pandemic the prevalence of diabetes elevated less than expected.We concluded that the prevalence of diabetes increased slowly during the pandemic than expected.
In addition, prior studies demonstrated how COVID-19 impacted on diabetes and vice versa.However, its association mostly focused on pathology 20 , not socioeconomic factors.Since diabetes is caused by the multifactorial interplay among social, environmental, and genetic factors, there is a need to investigate the association between the prevalence of diabetes and variables at the individual and social levels before and during the pandemic.

Possible mechanisms
This study showed a significant deceleration in the total number of patients with diagnosed diabetes during the pandemic.It may be driven by the reluctance of hospital visits.Some previous studies noted that 41% reported having avoided medical care due to concerns about COVID-19 21 .If this tendency were to be maintained for a long time, people would lose chances to manage chronic diseases and detect new conditions, which may aggravate health outcomes.
Also, during the pandemic, the number of people diagnosed with diabetes is fewer than expected among underprivileged individuals.We speculate that the actual population suffering from diabetes is slightly different from those diagnosed with diabetes, especially during the pandemic.The pandemic has magnified disparities in access to health services and lack of control over the allocation of health resources.The already vulnerable communities had difficulties in access to physician consultation, although telemedicine was temporarily allowed www.nature.com/scientificreports/ in delayed disease diagnosis among racial and ethnic minorities in the US 25 .Thus, the pandemic may have contributed to further rises in the under-diagnosis of diabetes among the already vulnerable groups 26 .

Policy implications
We interpreted that low-income, low educational levels, high BMI, and infrequent walking groups have underdiagnosed diabetes since the outbreak of COVID-19, compared with the pre-pandemic era.Since some studies reported that early detection of diabetes decreases cardiovascular morbidity and mortality 27 , the importance of early diagnosis of diabetes cannot be ignored.A sustainable response is needed at the policy level, such as

Conclusions
This study examined trends in the prevalence of type 2 diabetes in the Korean population from 2009 to 2021 and the associations between the prevalence of diabetes and each risk factor before and during the pandemic.During the pandemic, the prevalence of diagnosed diabetes increased slowly compared to the pre-pandemic era.Moreover, a lower occurrence of diagnosed diabetes was observed in men, those with high-income, highlevel education groups, and those with frequent walking habits during the pandemic.The pandemic seemed to attenuate access to healthcare and an unprecedented increase in under-diagnosis among the minority. https://doi.org/10.1038/s41598-023-43353-x

FrequencyFigure 1 .
Figure 1.Ratio of ORs plot for association between the prevalence of diabetes and each socioeconomic and behavioral factor including sex, education background, region of residence, BMI, income, and frequency of walking.Blue dots indicate ratio of ORs; Error bars indicate 95% CIs.BMI body mass index, CI confidence interval, OR odds ratio.

Figure 2 .
Figure 2. Regional trend of the prevalence of diabetes amongst (A) rural and (B) urban regions, 2009 to 2021.

Figure 4 .
Figure 4. Regional difference of the diabetes prevalence before and during the pandemic in South Korea, 2018-2019 versus 2020-2021.

Table 2 .
National trend of the prevalence of diagnosed diabetes before and during the COVID-19 pandemic, weighted % (95% CI).BMI body mass index, CI confidence interval.Numbers in bold indicate a significant difference (P < 0.05).

Table 3 .
Ratio of ORs for association between the prevalence of diabetes and each socioeconomic and behavioral factor.BMI body mass index, CI confidence interval, OR odds ratio.Bold numbers indicate a significant difference (P < 0.05).