Saturation is commonly used to determine sample sizes in qualitative research, yet there is little guidance on what influences saturation. We aimed to assess saturation and identify parameters to estimate sample sizes for focus group studies in advance of data collection. We used two approaches to assess saturation in data from 10 focus group discussions. Four focus groups were sufficient to identify a range of new issues (code saturation), but more groups were needed to fully understand these issues (meaning saturation). Group stratification influenced meaning saturation, whereby one focus group per stratum was needed to identify issues; two groups per stratum provided a more comprehensive understanding of issues, but more groups per stratum provided little additional benefit. We identify six parameters influencing saturation in focus group data: study purpose, type of codes, group stratification, number of groups per stratum, and type and degree of saturation.

Type 2 diabetes mellitus (T2DM) is one of the leading causes of morbidity and mortality. While all ethnic groups are affected, the prevalence of T2DM in South Asians, both in their home countries and abroad, is extremely high and is continuing to rise rapidly. Innate biological susceptibilities coupled with rapid changes in physical activity, diet, and other lifestyle behaviors are contributing factors propelling the increased burden of disease in this population. The large scope of this problem calls for investigations into the cause of increased susceptibility and preventative efforts at both the individual and population level that are aggressive, culturally sensitive, and start early. In this review, we outline the biological and environmental factors that place South Asians at elevated risk for T2DM, compared with Caucasian and other ethnic groups.

Real-world LSM strategies can reduce diabetes risk, even with small weight reductions.

OBJECTIVEThis study tests the effectiveness of expert guidelines for diabetes prevention: lifestyle intervention with addition of metformin, when required, among people with prediabetes.RESEARCH DESIGN AND METHODSThe Diabetes Community Lifestyle Improvement Program (D-CLIP) is a randomized, controlled, translation trial of 578 overweight/obese Asian Indian adults with isolated impaired glucose tolerance (iIGT), isolated impaired fasting glucose (iIFG), or IFG+IGT in Chennai, India. Eligible individuals were identified through community-based recruitment and randomized to standard lifestyle advice (control) or a 6-month, culturally tailored, U.S. Diabetes Prevention Program–based lifestyle curriculum plus stepwise addition of metformin (500 mg, twice daily) for participants at highest risk of conversion to diabetes at ≥4 months of follow-up. The primary outcome, diabetes incidence, was assessed biannually and compared across study arms using an intention-to-treat analysis.RESULTSDuring 3 years of follow-up, 34.9% of control and 25.7% of intervention participants developed diabetes (P = 0.014); the relative risk reduction (RRR) was 32% (95% CI 7–50), and the number needed to treat to prevent one case of diabetes was 9.8. The RRR varied by prediabetes type (IFG+IGT, 36%; iIGT, 31%; iIFG, 12%; P = 0.77) and was stronger in participants 50 years or older, male, or obese. Most participants (72.0%) required metformin in addition to lifestyle, although there was variability by prediabetes type (iIFG, 76.5%; IFG+IGT, 83.0%; iIGT, 51.3%).CONCLUSIONSStepwise diabetes prevention in people with prediabetes can effectively reduce diabetes incidence by a third in community settings; however, people with iIFG may require different interventions.

IMPORTANCE Diabetes prevention is imperative to slow worldwide growth of diabetes-related morbidity and mortality. Yet the long-term efficacy of prevention strategies remains unknown.OBJECTIVE To estimate aggregate long-term effects of different diabetes prevention strategies on diabetes incidence.DATA SOURCES Systematic searches of MEDLINE, EMBASE, Cochrane Library, and Web of Science databases. The initial search was conducted on January 14, 2014, and was updated on February 20, 2015. Search terms included prediabetes, primary prevention, and risk reduction.STUDY SELECTION Eligible randomized clinical trials evaluated lifestyle modification (LSM) and medication interventions (>6 months) for diabetes prevention in adults (age Ն18 years) at risk for diabetes, reporting between-group differences in diabetes incidence, published between January 1, 1990, and January 1, 2015. Studies testing alternative therapies and bariatric surgery, as well as those involving participants with gestational diabetes, type 1 or 2 diabetes, and metabolic syndrome, were excluded. DATA EXTRACTION AND SYNTHESISReviewers extracted the number of diabetes cases at the end of active intervention in treatment and control groups. Random-effects meta-analyses were used to obtain pooled relative risks (RRs), and reported incidence rates were used to compute pooled risk differences (RDs). MAIN OUTCOMES AND MEASURESThe main outcome was aggregate RRs of diabetes in treatment vs control participants. Treatment subtypes (ie, LSM components, medication classes) were stratified. To estimate sustainability, post-washout and follow-up RRs for medications and LSM interventions, respectively, were examined. RESULTS Forty-three studies were included and pooled in meta-analysis (49 029 participants; mean [SD] age, 57.3 [8.7] years; 48.0% [n = 23 549] men): 19 tested medications; 19 evaluated LSM, and 5 tested combined medications and LSM. At the end of the active intervention (range, 0.5-6.3 years), LSM was associated with an RR reduction of 39% (RR, 0.61; 95% CI, 0.54-0.68), and medications were associated with an RR reduction of 36% (RR, 0.64; 95% CI, 0.54-0.76). The observed RD for LSM and medication studies was 4.0 (95% CI, 1.8-6.3) cases per 100 person-years or a number-needed-to-treat of 25. At the end of the washout or follow-up periods, LSM studies (mean follow-up, 7.2 years; range, 5.7-9.4 years) achieved an RR reduction of 28% (RR, 0.72; 95% CI, 0.60-0.86); medication studies (mean follow-up, 17 weeks; range, 2-52 weeks) showed no sustained RR reduction (RR, 0.95; 95% CI, 0.79-1.14). CONCLUSIONS AND RELEVANCEIn adults at risk for diabetes, LSM and medications (weight loss and insulin-sensitizing agents) successfully reduced diabetes incidence. Medication effects were short lived. The LSM interventions were sustained for several years; however, their effects declined with time, suggesting that interventions to preserve effects are needed.

OBJECTIVETo determine A1C cut points for glucose intolerance in Asian Indians.RESEARCH DESIGN AND METHODSA total of 2,188 participants without known diabetes were randomly selected from the Chennai Urban Rural Epidemiology Study. All had fasting plasma glucose (FPG) and 2-h postload plasma glucose measurements after a 75-g load and were classified as having impaired fasting glucose (IFG) (American Diabetes Association [ADA] criteria, FPG ≥5.5 and <7 mmol/l, and World Health Organization [WHO] criteria, FPG ≥6.1 and <7 mmol/l), impaired glucose tolerance (IGT) (2-h postload plasma glucose ≥7.8 and <11.1 mmol/l), or diabetes (FPG ≥7 mmol/l and/or 2-h postload plasma glucose ≥11.1 mmol/l). A1C was measured using the Bio-Rad Variant machine. Based on receiver operating characteristic curves, optimum sensitivity and specificity were derived for defining A1C cut points for diabetes, IGT, and IFG.RESULTSMean ± SD values of A1C among subjects with normal glucose tolerance, IGT, and diabetes were 5.5 ± 0.4, 5.9 ± 0.6, and 8.3 ± 2.0%, respectively (Ptrend < 0.001) with considerable overlap. To identify diabetes based on 2-h postload plasma glucose, the A1C cut point of 6.1% had an area under the curve (AUC) of 0.941 with 88.0% sensitivity and 87.9% specificity. When diabetes was defined as FPG ≥7.0 mmol/l, the A1C cut point was 6.4% (AUC = 0.966, sensitivity 93.3%, and specificity 92.3%). For IGT, AUC = 0.708; for IFG, AUC = 0.632 (WHO criteria) and 0.708 (ADA criteria), and the A1C cut point was 5.6%.CONCLUSIONSIn Asian Indians, A1C cut points of 6.1 and 6.4% defined diabetes by 2-h postload plasma glucose or FPG criteria, respectively. A value of 5.6% optimally identified IGT or IFG but was <70% accurate.

Diabetes is a costly disease affecting 387 million individuals globally and 28 million in the United States. Its precursor, prediabetes, affects 316 and 86 million individuals globally and in the United States, respectively. People living with elevated blood glucose levels are at high risk for all-cause mortality and numerous cardiometabolic ailments. Fortunately, diabetes can be prevented or delayed by maintaining a healthy lifestyle and a healthy body weight. In this review, we summarize the literature around lifestyle diabetes prevention programs and provide recommendations for introducing prevention strategies in clinical practice. Overall, evidence supports the efficacy and effectiveness of lifestyle diabetes prevention interventions across clinical and community settings, delivery formats (eg, individual-, group-, or technology-based), and implementers (eg, clinicians, community members). Evidence-based diabetes prevention strategies that can be implemented in clinical practice include brief behavior change counseling, group-based education, community referrals, and health information technologies. These strategies represent opportunities where practitioners, communities, and health care systems can work together to provide individuals with education, support and opportunities to maintain healthy, diabetes-free lifestyles.

Cardiovascular, respiratory, and related disorders (CVRDs) are the leading causes of adult death worldwide, and substantial inequalities in care of patients with CVRDs exist between countries of high income and countries of low and middle income. Based on current trends, the UN Sustainable Development Goal to reduce premature mortality due to CVRDs by a third by 2030 will be challenging for many countries of low and middle income. We did systematic literature reviews of effectiveness and cost-effectiveness to identify priority interventions. We summarise the key findings and present a costed essential package of interventions to reduce risk of and manage CVRDs. On a population level, we recommend tobacco taxation, bans on trans fats, and compulsory reduction of salt in manufactured food products. We suggest primary health services be strengthened through the establishment of locally endorsed guidelines and ensured availability of essential medications. The policy interventions and health service delivery package we suggest could serve as the cornerstone for the management of CVRDs, and afford substantial financial risk protection for vulnerable households. We estimate that full implementation of the essential package would cost an additional US$21 per person in the average low-income country and $24 in the average lower-middle-income country. The essential package we describe could be a starting place for low-income and middle-income countries developing universal health coverage packages. Interventions could be rolled out as disease burden demands and budgets allow. Our outlined interventions provide a pathway for countries attempting to convert the UN Sustainable Development Goal commitments into tangible action.