Health care access and glycemic control in youth and young adults with type 1 and type 2 diabetes in South Carolina

Diabetes distress, depression, and future glycemic control among adolescents with type 1 diabetes

OBJECTIVES

Increased diabetes distress and depression in adolescents with type 1 diabetes (T1D) are associated with poor glycemic control but it is not known whether they predict future glycemic control.

METHODS

Patient Health Questionnaire (PHQ-9) and Problem Areas in Diabetes-Teen version (PAID-T) scores were given to 275 adolescents (age 13-17 years) with T1D. Robust rank order multivariate regression analysis was used to assess how age, duration of diabetes diagnosis, HbA1c at screen, PHQ-9 score, PAID-T screen, and insurance status predicted HbA1c at 1, 2, and 3 years after, and the changes in HbA1c over time.

RESULTS

HbA1c and changes in HbA1c after one year were related to baseline HbA1c. At 2 and 3 years HbA1c was related to the initial HbA1c [β: 0.64 (95 % CI 0.53-0.75) and β: 0.47 (95 % CI 0.33-0.61), respectively], and to PHQ9 at screening [β: 0.07 (95 % CI 0.01-0.14) and β: 0.11 (95% CI 0.03-0.18), respectively]. Relationships were also demonstrated between PHQ9 and changes HbA1c after 2 and 3 years [β: 0.07 (95% CI 0.01-0.14) and β: 0.11 (95 % CI 0.03-0.18), respectively]. PAID-T score was not related to future glycemic control or changes in glycemic control at any time. Insurance status (private 1, public 2) also predicted future glycemic control and changes in HbA1c at 1, 2, and 3 years too.

CONCLUSIONS

Higher PHQ9 scores and public insurance predict worsening glycemic control over 3 years in adolescents with T1D while increased diabetes distress does not.

Social and Structural Determinants of Cardiovascular Complications of Diabetes

PURPOSE OF REVIEW

Cardiovascular disease (CVD) is the leading cause of mortality in people who have diabetes. Racial and ethnic minorities with diabetes have suboptimal management of cardiovascular risk factors, leading to higher mortality. Social and structural determinants of health are external factors that influence an individual's ability to choose positive health behaviors. In this review, we will discuss cardiovascular complications in people who have diabetes and their relationship to social determinants of health (SDOH).

RECENT FINDINGS

Recent innovations in diabetes treatment, including new devices and medications, have improved care and survival. However, disparities in the availability of these treatments to racial and ethnic minorities may contribute to continued inequities in CVD outcomes. Racial/ethnic disparities in CVD relate to inequities in economic opportunity, education and health literacy, neighborhoods and social cohesion, and health care access and quality driven by structural racism.

Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus living in Puerto Rico

This is a descriptive study using healthcare claims data from patients with T2DM from public and private healthcare insurance companies providing services in Puerto Rico in 2013, aimed to estimate the prevalence of comorbidities in this population. Descriptive analyses were performed by sociodemographic, and type of service variables using frequency and percent for categorical data or means (+/-SD) or median (IQR) for continuous variables. Chi-square, Fisher exact or two-sample t-tests were used for comparisons. A total of 3,100,636 claims were identified from 485,866 adult patients with T2DM. Patients older than 65 years represented 48% of the study population. Most patients were women (57%) and had private health insurance (77%). The regions of Metro Area (17%) and Caguas (16%) had the higher number of persons living with T2DM. The overall estimated prevalence of T2DM was 17.4%. The number of claims per patient ranged from 1 to 339. A mean of 6.3 claims (SD±9.99) and a median of 3 claims (Q1 1- Q3 8) per subject were identified. Of the 3,100,636 claims most (74%) were related to the diagnosis of diabetes (59%) and associated to outpatient services (88%). The most prevalent comorbidities were hypertension (48%), hyperlipidemia (41%), neuropathy (21%); renal disease (15%), and retinopathy (13%). A high prevalence and co-prevalence of comorbidities and use of healthcare services were identified in patients with T2DM, especially in older adults. Since most comorbidities were due to diabetes-related conditions, this analysis highlights the importance of early diagnosis and adequate management of T2DM patients to avoid preventable burden to the patient and to the healthcare system.

Social determinants of health and glycemic control in persons with type 2 diabetes mellitus attending a tertiary hospital in Nepal: A cross-sectional study

Background

Diabetes mellitus (DM) is an emerging global public health challenge worldwide, including Nepal. Social determinants of health (SDOH) play a major role in glycemic control among persons with type 2 DM (T2DM). However, little is known about the association between SDOH and glycemic control among individuals with T2DM in Nepal.

Objective

This study aimed to identify the level of glycemic control and SDOH associated with glycemic control among Nepalese with T2DM.

Methods

This cross-sectional study was conducted at a tertiary hospital in Kathmandu, Nepal, among 135 Nepalese diagnosed with T2DM who attended follow-up appointments. Convenience sampling and inclusion criteria were utilized for participant selection. Data were collected from April to June 2021 using validated scales. Descriptive statistics, Chi-square test, and binary logistic regression were employed to analyze the data.

Results

The mean age of the participants in this study was 53.84 (SD = 11.78) years, and the average monthly household income was 567.64 (SD = 362.30) USD. The majority of the participants (77.8%) were literate and had no health insurance coverage (73.3%). Approximately 64.4% of the participants showed suboptimal glycemic control indicated by glycated hemoglobin (HbA1c) ≥7%. The significant determinants of good glycemic control included monthly household income of >850 USD (odds ratio [OR] = 12.20, 95% confident interval [CI] = 1.76-84.61, p = 0.011) and 341-600 USD (OR = 7.64, 95% CI 1.35-42.98, p = 0.021), being literate (OR = 6.37, 95% CI = 1.65-24.49, p = 0.007), having health insurance (OR = 5.82, 95% CI = 1.49-22.65, p = 0.011), sufficient health literacy (OR = 3.46, 95% CI = 1.10-10.83, p = 0.03), and high (OR = 16.17, 95% CI = 2.36-110.67, p = 0.005) and moderate (OR = 7.02, 95% CI = 1.26-39.07, p = 0.026) food availability, respectively.

Conclusion

The study revealed suboptimal glycemic control in Nepalese with T2DM. This study presents essential social determinants of glycemic control in this population. Therefore, healthcare providers, particularly nurses, should pay more attention to assessing social determinants and provide targeted interventions to patients with T2DM who have low income, are illiterate, have no health insurance coverage, have insufficient health literacy, and have low resources for food availability.

Cardiovascular disease and risk factors in adults with diabetes mellitus in Hungary: a population-based study

Introduction

Diabetes mellitus (DM) and cardiovascular disease (CVD) such as acute myocardial infarction, stroke, and coronary artery disease are highly prevalent conditions that are responsible for significant morbidity and mortality, particularly in Hungary. The conditions are attributed to identical risk factors, and individuals with DM are primarily susceptible to cardiovascular complications, which are the leading causes of death and disability in patients with DM. The objective of this study was to estimate the prevalence of CVD in individuals with DM and to investigate the association between potential risk factors and the presence of CVD among individuals with DM in a population-based sample.

Methods

The study was based on data from three waves of the European Health Interview Surveys (EHIS) conducted in Hungary in 2009, 2014, and 2019.

Results

The prevalence of CVD among patients with DM decreased during the study period and that socioeconomic factors, cardiometabolic risk factors including high blood pressure and high cholesterol, and depression are major contributors to CVD burden in patients with DM in Hungary.

Discussion

Our findings suggest the importance of regular check-up for hypertension and hypercholesterolemia, better focus on socioeconomic status, as well as ongoing monitoring of mental health among patients with diabetes. Further research is needed to understand the potential causes behind the observed decrease in CVD prevalence.

Adolescents with Type 2 Diabetes: Overcoming Barriers to Effective Weight Management

The prevalence of type 2 diabetes (T2DM) among children and adolescents has remarkably increased in the last two decades, particularly among ethnic minorities. Management of T2DM is challenging in the adolescent population due to a constellation of factors, including biological, socioeconomic, cultural, and psychological barriers. Weight reduction is an essential component in management of T2DM as weight loss is associated with improvement in insulin sensitivity and glycemic status. A family centered and culturally appropriate approach offered by a multidisciplinary team is crucial to address the biological, psychosocial, cultural, and financial barriers to weight management in youth with T2DM. Lifestyle interventions and pharmacotherapy have shown modest efficacy in achieving weight reduction in adolescents with T2DM. Bariatric surgery is associated with excellent weight reduction and remission of T2DM in youth. Emerging therapies for weight reduction in youth include digital technologies, newer GLP-1 agonists and endoscopic procedures.

Evaluation of an Integrated Intervention to Address Clinical Care and Social Needs Among Patients with Type 2 Diabetes

BACKGROUND

The Providence Diabetes Collective Impact Initiative (DCII) was designed to address the clinical challenges of type 2 diabetes and the social determinants of health (SDoH) challenges that exacerbate disease impact.

OBJECTIVE

We assessed the impact of the DCII, a multifaceted intervention approach to diabetes treatment that employed both clinical and SDoH strategies, on access to medical and social services.

DESIGN

The evaluation employed a cohort design and used an adjusted difference-in-difference model to compare treatment and control groups.

PARTICIPANTS

Our study population consisted of 1220 people (740 treatment, 480 control), aged 18-65 years old with a pre-existing type 2 diabetes diagnosis who visited one of the seven Providence clinics (three treatment and four control) in the tri-county area of Portland, Oregon, between August 2019 and November 2020.

INTERVENTIONS

The DCII threaded together clinical approaches such as outreach, standardized protocols, and diabetes self-management education and SDoH strategies including social needs screening, referral to a community resource desk, and social needs support (e.g., transportation) to create a comprehensive, multi-sector intervention.

MAIN MEASURES

Outcome measures included SDoH screens, diabetes education participation, HbA1c, blood pressure, and virtual and in-person primary care utilization, as well as inpatient and emergency department hospitalization.

KEY RESULTS

Compared to patients at the control clinics, patients at DCII clinics saw an increase in diabetes education (15.5%, p<0.001), were modestly more likely to receive SDoH screening (4.4%, p<0.087), and had an increase in the average number of virtual primary care visits of 0.35 per member, per year (p<0.001). No differences in HbA1c, blood pressure, or hospitalization were observed.

CONCLUSIONS

DCII participation was associated with improvements in diabetes education use, SDoH screening, and some measures of care utilization.

Trends in Use of High-Cost Antihyperglycemic Drugs Among US Adults with Type 2 Diabetes

BACKGROUND

Some antihyperglycemic drugs can reduce cardiovascular events, slow the progression of kidney disease, and prevent death, but they are more expensive than older drugs.

OBJECTIVES

(1) To estimate trends in use of antihyperglycemic drugs by cost; (2) to examine use of high-cost drugs by race/ethnicity, income, and insurance status DESIGN: Cross-sectional analysis of the 2003-2018 National Health and Nutrition Examination Survey PARTICIPANTS: US adults ≥18 years with type 2 diabetes EXPOSURES: Race/ethnicity, income, and insurance status MAIN MEASURES: Low-cost noninsulin medications included any drugs that had at least one generic version approved by the Food and Drug Administration. Human regular, NPH, and premixed NPH/regular 70/30 insulins were classified as low-cost. All other noninsulin medications and insulins were considered high-cost KEY RESULTS: The sample included 7,394 patients. Prevalence of use of low-cost noninsulin drugs increased from 37% in 2003-2004 to 52% in 2017-2018. Use of high-cost noninsulin drugs decreased from 2003-2004 to 2013-2014 and then slowly increased. Use of low-cost insulin decreased from 7 to 2% while high-cost insulin rose from 4 to 16%. In multivariable analysis, non-White patients had 25-35% lower odds of receiving high-cost drugs than non-Hispanic Whites. Health insurance was associated with more than twice the odds of having high-cost drugs compared to no insurance. Patients with higher HbA1c or moderate obesity were also more likely to use high-cost drugs. Sex, income, and insurance type were not associated with receipt of high-cost drugs.

CONCLUSIONS

There was a shift in utilization from high- to low-cost noninsulin drugs, but since 2013-2014 the trend has slowly reversed with increased use of newer, more expensive drug classes. High-cost insulin analogs have almost completely replaced lower cost human insulins. Disparities in receipt of diabetes drugs by race/ethnicity and insurance must be addressed to ensure that cost is not a barrier for disadvantaged populations.

Inequalities in Glycemic Control in Youth with Type 1 Diabetes Over Time: Intersectionality Between Socioeconomic Position and Race and Ethnicity

BACKGROUND

Racial/ethnic health inequities have been well-documented among youth and young adults with type 1 diabetes (T1D), yet little is known about how socioeconomic position (SEP) intersects with the risk marker of race/ethnicity to predict inequities in longitudinal glycemic control.

PURPOSE

To identify patterns of SEP, race/ethnicity, and clinical characteristics that differentiate hemoglobin A1c (HbA1c) trajectories among youth and young adults after T1D diagnosis.

METHODS

The SEARCH for Diabetes in Youth cohort includes youth with diabetes diagnosed from 2002 to 2006 and 2008 who were followed through 2015. We analyzed data from 1,313 youth and young adults with T1D with ≥3 HbA1c measures. Classification tree analysis identified patterns of baseline demographic, SEP, and clinical characteristic that best predicted HbA1c trajectories over an average of 8.3 years using group-based trajectory modeling.

RESULTS

Two HbA1c trajectories were identified: Trajectory 1 (77%) with lower baseline HbA1c and mild increases (from mean 7.4% to 8.4%) and Trajectory 2 (23%) with higher baseline HbA1c and major increases (from 8.5% to 11.2%). Race/ethnicity intersected with different SEP characteristics among non-Hispanic white (NHW) than in non-whites. Public health insurance predicted high-risk Trajectory 2 membership in non-whites, whereas parental education, household structure, diagnosis age and glucose checking frequency predicted membership for NHW youth and young adults. Two characteristics, race/ethnicity and parental education alone identified 80% of the Trajectory 2 members.

CONCLUSIONS

Race/ethnicity intersects with multiple SEP and clinical characteristics among youth and young adults with T1D, which is associated with particularly high risk of poor long-term glycemic control.

Impact of the COVID-19 pandemic on management of children and adolescents with Type 1 diabetes

BACKGROUND

The coronavirus disease-2019 (COVID-19) pandemic had widespread impacts on the lives of parents and children. We determined how the pandemic affected Type 1 diabetes patients at a large urban pediatric teaching hospital.

METHODS

We compared patient characteristics, glycemic control, PHQ-9 depression screen, in person and virtual outpatient encounters, hospitalizations and continuous glucose monitor (CGM) utilization in approximately 1600 patients in 1 year periods preceding and following the local imposition of COVID-related restrictions on 3/15/2020 ("2019" and "2020" groups, respectively).

RESULTS

In a generalized linear model, increasing age, non-commercial insurance, Black and Hispanic race/ethnicity, and non-utilization of CGMs were all associated with higher hemoglobin A1c (HbA1c), but there was no difference between the 2019 and 2020 groups. The time in range in CGM users was lower with non-commercial insurance and in Black and Hispanic patients; it improved slightly from 2019 to 2020. CGM utilization by patients with non-commercial insurance (93% of such patients were in government programs, 7% uninsured or "other") increased markedly. In 2020, patients with commercial insurance (i.e., private-pay or provided by an employer) had fewer office visits, but insurance status did not influence utilization of the virtual visit platform. There was no change in hospitalization frequency from 2019 to 2020 in either commercially or non-commercially insured patients, but patients with non-commercial insurance were hospitalized at markedly higher frequencies in both years. PHQ-9 scores were unchanged.

CONCLUSIONS

Hospitalization frequency, glycemic control and depression screening were unchanged in our large urban pediatric teaching hospital during the COVID pandemic. Increased utilization of CGM and rapid adoption of telemedicine may have ameliorated the impact of the pandemic on disease management.

Demographic characteristics and acute complications among adults with type 1 diabetes: Comparison of two multicentre databases from Germany and the United States

BACKGROUND

Studies on acute complications in adult T1D were previously reported from the United States (U.S.) and from Germany. The aim was to compare demographic characteristics and patterns of severe hypoglycaemia (SH) and diabetic ketoacidosis (DKA) between Germany and the U.S.

METHODS

Descriptive comparison on individuals aged ≥18 years, with T1D duration ≥2 years were made between the German diabetes-patient registry (DPV) and the U.S. electronic-health-record database (T1PCO). Individuals in both databases were divided into patients with haemoglobin A1c (HbA1c) <7% and HbA1c ≥7%.

RESULTS

5190 (DPV) and 31,430 individuals (T1PCO) fulfilled the inclusion criteria. DPV patients were younger, more often male and had lower body-mass index. In both databases, more males than females had HbA1c <7%. Individuals had higher HbA1c in T1PCO compared to DPV. The relationship between HbA1c and DKA was similar in both databases. SH revealed a U-shaped curve in T1PCO, but no clear pattern was present in DPV. SH events increased with higher age in DPV, but not in T1PCO.

CONCLUSION

Patterns of SH differ between Germany and U.S. Differences in capture of SH among the databases cannot be excluded, but differences in health care including patient education and level of care by specialists are likely.

Distance from the endocrinology clinic and diabetes control in a rural pediatric population

OBJECTIVE

We analyzed the impact of geographic distance from the clinic on adherence to recommended clinic visits and diabetes control among patients with type 1 diabetes (T1D) seen in a pediatric endocrinology clinic serving a rural region in eastern North Carolina.

METHODS

We retrospectively included patients with T1D age ≤20 years seen in our clinic during 2017. Outcomes were tracked until June 2018. Distance from the clinic was determined according to the zone improvement plan (ZIP) code of patient address. Visit adherence was defined based on the number of attended visits during the study period, aiming for 1 every 3 months. Glycated hemoglobin (HbA1c) was measured at the first and last visits during the review period.

RESULTS

The analysis included 368 patients, of whom 218 (59%) completed at least 1 visit every 3 months. The median HbA1c was 9.1 (interquartile range [IQR]: 8.0, 10.3) at the initial visit, and 9.3 (IQR: 8.0, 11.1) at the final visit. Median distance from the clinic was 56 km (IQR: 35, 86). On multivariable logistic regression, greater distance from the clinic was associated with lower odds of visit adherence (odds ratio per 10 km: 0.93; 95% confidence interval: 0.87, 0.99; p=0.030). Neither distance to the clinic nor clinic visit adherence were associated with HbA1c.

CONCLUSIONS

Patients living further away from the clinic were less likely to adhere to the recommended visit schedule, but distance was not correlated with HbA1c levels. Further work is needed to assist families living far from the clinic with adhering to recommended visits.

Socioeconomic position is associated with glycemic control in youth and young adults with type 1 diabetes

OBJECTIVE

Health inequities persist in youth and young adults (YYA) with type 1diabetes in achieving optimal glycemic control. The purpose of this study was to assess the contribution of multiple indicators of social need to these inequities.

RESEARCH DESIGN AND METHODS

Two hundred and twenty two YYA withtype 1 diabetes enrolled in the SEARCH Food Insecurity Study in South Carolina and Washington between the years 2013 and 2015 were included. Latent class analysis was used to identify socioeconomic profiles based on household income, parental education, health insurance, household food insecurity, and food assistance. Profiles were evaluated in relation to glycemic control using multivariable linear and logistic regression, with HbA1c > 9%(75 mmol/mol) defined as high-risk glycemic control.

RESULTS

Two profiles were identified: a lower socioeconomic profile included YYA whose parents had lower income and/or education, and were more likely to be uninsured, receive food assistance, and be food insecure. A higher socioeconomic profile included YYA whose circumstances were opposite to those in the lower socioeconomic profile. Those with a lower socioeconomic profile were more likely to have high-risk glycemic control relative to those with a higher socioeconomic profile (OR = 2.24, 95%CI = 1.16-4.33).

CONCLUSIONS

Lower socioeconomic profiles are associated with high-risk glycemic control among YYA with type 1 diabetes. This supports recommendations that care providers of YYA with type 1 diabetes assess individual social needs in tailoring diabetes management plans to the social context of the patient.

Dietary strategies to manage diabetes and glycemic control in youth and young adults with youth-onset type 1 and type 2 diabetes: The SEARCH for diabetes in youth study

AIMS

Examine associations of dietary strategies used to manage diabetes over time with hemoglobin A1c in youth-onset type 1 or type 2 diabetes.

METHODS

The SEARCH for Diabetes in Youth observational study assessed dietary strategies used by 1814 participants with diabetes (n = 1558 type 1, n = 256 type 2) at two to three research visits over 5.5 years (range 1.7-12.2). Participants reported often, sometimes, or never using 10 different dietary strategies, and use over time was categorized into five mutually exclusive groups: often using across visits; started using at later visits; sometimes using across visits; stopped using at later visits; or never using across visits. General multivariable linear models evaluated most recent A1c by use category for each strategy.

RESULTS

In type 1 diabetes, A1c was lower among those who starting tracking calories (-0.4%, Tukey P < .05), often counted carbs (-0.8%, Tukey P < .001), or sometimes chose low glycemic index foods (-0.5%, Tukey P = .02) vs those with less use, while participants who never drank more milk had the lowest A1c (-0.5%, Tukey P = .04). In type 2 diabetes, A1c was lower among those who often limited high fat foods (-2.0%, Tukey P = .02) or started counting carbohydrates (-1.7%, Tukey P = .07) than those who did so less.

CONCLUSIONS

For several dietary strategies, more frequent use over time was related to lower A1c in youth-onset type 1 and type 2 diabetes, suggesting these strategies can likely support diabetes management for this population. Investigation into factors predicting receipt of advice for specific strategies and corresponding impact on intake might be considered.

A Mobile-Based Intervention for Glycemic Control in Patients With Type 2 Diabetes: Retrospective, Propensity Score-Matched Cohort Study

Background

Mobile-based interventions appear to be promising in ameliorating huge burdens experienced by patients with type 2 diabetes. However, it is unclear how effective mobile-based interventions are in glycemic management of patients with type 2 diabetes based on real-world evidence.

Objective

This study aimed to evaluate the effectiveness of a mobile-based intervention on glycemic control in patients with type 2 diabetes based on real-world population data.

Methods

This retrospective, propensity score-matched cohort study analyzed longitudinal data from a clinical electronic health database. The study population included 37,913 patients with type 2 diabetes at cohort entry between October 1, 2016, and July 31, 2018. A total of 2400 patients were matched 1:1, using propensity score matching, into the usual care and mobile health (mHealth) groups. The primary outcomes of glycemic control included control rates of glycated hemoglobin (HbA_1c), fasting blood glucose (FBG), and postprandial 2-hour blood glucose (P2BG). Mean values and variation trends of difference with 95% CI were the secondary outcomes. The general linear model was used to calculate repeated-measures analyses of variance to examine the differences between the two groups. Subgroup and sensitivity analyses were performed.

Results

Of the 2400 patients included in the analysis, 1440 (60.00%) were male and the mean age was 52.24 years (SD 11.56). At baseline, the control rates of HbA_1c, FBG, and P2BG in the mHealth and usual care groups were 45.75% versus 47.00% (P=.57), 38.03% versus 32.76% (P=.07), and 47.32% versus 47.89% (P=.83), respectively. At the 3-, 6-, 9-, and 12-month follow-ups, the mHealth group reported higher control rates of HbA_1c than did the usual care group: 69.97% versus 46.06% (P<.001), 71.89% versus 61.24% (P=.004), 75.38% versus 53.44% (P<.001), and 72.31% versus 46.70% (P<.001), respectively. At the four follow-up sessions, the control rates of FBG in the mHealth and usual care groups were statistically different: 59.24% versus 34.21% (P<.001), 56.61% versus 35.14% (P<.001), 59.54% versus 34.99% (P<.001), and 59.77% versus 32.83% (P<.001), respectively. At the four follow-up sessions, the control rates of P2BG in the mHealth group were statistically higher than in the usual care group: 79.72% versus 48.75% (P<.001), 80.20% versus 57.45% (P<.001), 81.97% versus 54.07% (P<.001), and 76.19% versus 54.21% (P=.001), respectively. At the four follow-up sessions, the percentages of HbA_1c reduction in the mHealth group were 8.66% (95% CI 6.69-10.63), 10.60% (95% CI 8.66-12.54), 10.64% (95% CI 8.70-12.58), and 8.11% (95% CI 6.08-10.14), respectively. At the four follow-up sessions, the percentages of P2BG reduction in the mHealth group were 8.44% (95% CI 7.41-10.73), 17.77% (95% CI 14.98-20.23), 16.23% (95% CI 13.05-19.35), and 16.91% (95% CI 13.17-19.84), respectively. Starting from the sixth month, the mean HbA_1c and P2BG values in the two groups increased slightly.

Conclusions

This mobile-based intervention delivered by a multidisciplinary team can better improve glycemic control rates of patients with type 2 diabetes than usual care. These effects were best sustained within the first 6 months. Starting from the sixth month, intensive management needs to be conducted to maintain long-term effectiveness of the mobile-based intervention.