Type 1 diabetes mellitus care and education in China: The 3C study of coverage, cost, and care in Beijing and Shantou.

AIMS: The paucity of data on Type 1 diabetes in China hinders progress in care and policy-making. This study compares Type 1 diabetes care and clinical outcomes in Beijing and Shantou with current clinical guidelines. METHODS: The 3C Study was a cross-sectional study of the clinical practices and outcomes of people with Type 1 diabetes. The study sequentially enrolled 849 participants from hospital records, inpatient wards, and outpatient clinics. Data were collected via face-to-face interviews with patients and health professionals, the Summary of Diabetes Self-Care Activities, medical records, and venous blood samples. Care was audited using ISPAD/IDF indicators. Data underwent descriptive analysis and tests for association. RESULTS: The median age was 22years (IQR=13-34years), and 48.4% of the sample had diabetes less than six years. The median HbA1c was 8.5% (69mmol/mol) (IQR 7.2-10.5%), with significant regional variance (p=0.002). Insulin treatment was predominantly two injections/day (45% of patients). The highest incidence of diabetic ketoacidosis was 14.4 events/100 patient years among adolescents. Of the 57.3% of patients with LDL-C>2.6mmol/L, only 11.2% received treatment. Of the 10.6% considered hypertensive, 47.1% received treatment. Rates of documented screening for retinopathy, nephropathy, and peripheral neuropathy were 35.2%, 42.3%, and 25.0%, respectively. The median number of days of self-monitoring/week was 3.0 (IQR=1.0-7.0). There were significant differences in care practices across regions. CONCLUSIONS: The study documented an overall deficit in care with significant regional differences noted compared to practice guidelines. Modifications to treatment modalities and the structure of care may improve outcomes.

Global photographic assessment of men aged 18 to 60 years with male pattern hair loss receiving finasteride 1 mg or placebo.

BACKGROUND: Finasteride (1 mg) has been shown to increase vertex hair growth in men aged 18 to 60 years with male pattern hair loss and to increase frontal scalp hair growth in subjects aged 18 to 41 years. OBJECTIVE: A secondary efficacy analysis was conducted to determine effects of finasteride (1 mg) on scalp hair growth in the 4 distinct scalp regions affected by male pattern hair loss. METHODS: Multicenter, double-blind studies randomized patients with vertex hair loss (men aged 18-41 and 41-60 years) to finasteride (1 mg/d) or placebo. Efficacy was evaluated by review of standardized clinical photographs (global photographic assessment) of the vertex, anterior/mid scalp regions, and frontal and temporal hairlines over 24 months relative to baseline. RESULTS: At 24 months, treatment with finasteride resulted in statistically significant (P ≤ .05) hair growth versus placebo in all scalp regions. There was also a significant decrease in hair loss in the younger men treated with finasteride in all areas, but only in the vertex and anterior/mid scalp regions in the older men. A slightly higher incidence of drug-related sexual adverse experiences was reported in the finasteride group than in the placebo group, irrespective of age. LIMITATIONS: These studies enrolled men with vertex pattern hair loss; therefore, the findings may not be extrapolated to men with predominantly anterior/mid scalp, frontal, or temporal hair loss. CONCLUSION: Based on global photographic assessment, finasteride (1 mg) is able to increase hair growth in all areas of the scalp affected by male pattern hair loss.

The 3C study: coverage cost and care of type 1 diabetes in China--study design and implementation.

AIM: To describe coverage, cost and care of type 1 diabetes (T1D) in 2 regions of China--Beijing and Shantou--including: METHODS: This is a mixed-methods descriptive study with three arms--coverage, cost and care. It is taking place in 4 tertiary hospitals, 3 secondary hospitals and 4 primary health facilities in Beijing, and 2 tertiary hospitals, 2 secondary hospitals and 2 primary health centres in Shantou, China. Two additional hospitals are involved in the coverage arm of the study. T1D participants are recruited from a 3-year list generated by each hospital and from those attending the outpatient clinic or admitted to the inpatient ward. Participants also include health care professionals and government officials. To determine coverage of care, a list of people with T1D is being developed including information on diagnosis, age, sex and vital status. The age and sex distribution will be compared with the expected distribution. To estimate the economic burden of T1D three groups of costs will be calculated - direct medical costs, direct non-medical costs and indirect costs from different perspectives of analysis (patients and their families, health system, insurer and societal perspective). The data are being collected from people with T1D (patient-parents face-to-face interviews), hospital billing departments, medical records and government officials using a combined "top-down, bottom-up" approach developed to validate the data. Quality of life is assessed using the EQ-5D tool and burden of disease is measured based on clinical outcomes and complications. Standard care will be defined, costed and compared to the cost of current care identified within the study to determine the investment required to improve outcomes. The third arm includes three components - health policy, clinical care and education, and information management. Face-to-face, semi-structured interviews are conducted with people with T1D (for those <15 years of age parents are interviewed), health care professionals, senior hospital management and government officials. The core Summary of Diabetes Self-Care Activities Measure plus an additional 6 questions from the revised SDSCA scale are used to assess patient self-care. A medical records audit tool is used to assess care [7]. Clinical outcomes and self-care activities will be analysed for associations with care and education. Information management and care processes will be described using the Standard for Integration Definition for Function Modelling (IDEF0) [8]. PROGRESS TO DATE: At the time of writing (early October) the 3-year case list includes 1269 people with type 1 diabetes from Beijing and 481 people for Shantou, a total of 1750. In addition, two hundred and twenty people with T1D or their parents participated in face-to-face interviews in Beijing and 183 in Shantou, a total of 403. PRACTICAL PRELIMINARY CONCLUSIONS: Key implementation considerations were identified early in the project. Project success is dependent on strong local partnerships with local opinion leaders and key officials. It is important that a physician is the first point of contact to build the case list and recruit participants. July, August and January are peak months for recruiting school-age children in the Children's Hospital as this is school vacation period when they are more likely to attend clinics.

High impact actions: preventing falls and encouraging exercise.

This article, the second in a series on the NHS Institute for Innovation and Improvement's eight high impact actions, reviews the roles played by nurses and local organisations in preventing falls among older people through early intervention and the promotion of active lifestyles.

Cost and results of information systems for health and poverty indicators in the United Republic of Tanzania.

OBJECTIVE: To examine the costs of complementary information generation activities in a resource-constrained setting and compare the costs and outputs of information subsystems that generate the statistics on poverty, health and survival required for monitoring, evaluation and reporting on health programmes in the United Republic of Tanzania. METHODS: Nine systems used by four government agencies or ministries were assessed. Costs were calculated from budgets and expenditure data made available by information system managers. System coverage, quality assurance and information production were reviewed using questionnaires and interviews. Information production was characterized in terms of 38 key sociodemographic indicators required for national programme monitoring. FINDINGS: In 2002-03 approximately US$ 0.53 was spent per Tanzanian citizen on the nine information subsystems that generated information on 37 of the 38 selected indicators. The census and reporting system for routine health service statistics had the largest participating populations and highest total costs. Nationally representative household surveys and demographic surveillance systems (which are not based on nationally representative samples) produced more than half the indicators and used the most rigorous quality assurance. Five systems produced fewer than 13 indicators and had comparatively high costs per participant. CONCLUSION: Policy-makers and programme planners should be aware of the many trade-offs with respect to system costs, coverage, production, representativeness and quality control when making investment choices for monitoring and evaluation. In future, formal cost-effectiveness studies of complementary information systems would help guide investments in the monitoring, evaluation and planning needed to demonstrate the impact of poverty-reduction and health programmes.

Is it time to reassess the categorization of disease burdens in low-income countries?

The classification of disease burdens is an important topic that receives little attention or debate. One common classification scheme, the broad cause grouping, is based on etiology and health transition theory and is mainly concerned with distinguishing communicable from noncommunicable diseases. This may be of limited utility to policymakers and planners. We propose a broad care needs framework to complement the broad cause grouping. This alternative scheme may be of equal or greater value to planners. We apply these schemes to disability-adjusted life year estimates for 2000 and to mortality data from Tanzania. The results suggest that a broad care needs approach could shift the priorities of health planners and policymakers and deserves further evaluation.

Community-based monitoring of safe motherhood in the United Republic of Tanzania.

OBJECTIVE: To examine the progress made towards the Safe Motherhood Initiative goals in three areas of the United Republic of Tanzania during the 1990s. METHODS: Maternal mortality in the United Republic of Tanzania was monitored by sentinel demographic surveillance of more than 77,000 women of reproductive age, and by prospective monitoring of mortality in the following locations; an urban site; a wealthier rural district; and a poor rural district. The observation period for the rural districts was 1992-99 and 1993-99 for the urban site. FINDINGS: During the period of observation, the proportion of deaths of women of reproductive age (15-49 years) due to maternal causes (PMDF) compared with all causes was between 0.063 and 0.095. Maternal mortality ratios (MMRatios) were 591-1099 and maternal mortality rates (MMRates; maternal deaths per 100,000 women aged 15-49 years) were 43.1-123.0. MMRatios in surveillance areas were substantially higher than estimates from official, facility-based statistics. In all areas, the MMRates in 1999 were substantially lower than at the start of surveillance (1992 for rural districts, 1993 for the urban area), although trends during the period were statistically significant at the 90% level only in the urban site. At the community level, an additional year of education for household heads was associated with a 62% lower maternal death rate, after controlling for community-level variables such as the proportion of home births and occupational class. CONCLUSION: Educational level was a major predictor of declining MMRates. Even though rates may be decreasing, they remained high in the study areas. The use of sentinel registration areas may be a cost-effective and accurate way for developing countries to monitor mortality indicators and causes, including for maternal mortality.

Diabetes in Africa. Challenges to health care for diabetes in Africa.

The aim of this review is to summarize the contextual, clinical and health system challenges to the delivery of health care for diabetes in Africa. Planners need to allocate sufficient resources in a context where resources for health in general are insufficient. Choices need to be made between different options for health care within this context and mechanisms are required to facilitate the implementation of the selected options and ensure that quality of care is maintained.

Distribution of blood pressure, body mass index and smoking habits in the urban population of Dar es Salaam, Tanzania, and associations with socioeconomic status.

OBJECTIVE: To estimate the distribution of blood pressure (BP), body mass index (BMI), smoking habits and their associations with socioeconomic status (SES) in an urban population in early epidemiological transition. METHODS: Cross-sectional survey of the entire population aged 25-64 years in five branches of Dar es Salaam (Tanzania) through visits to all homes in the study area. Blood pressure was based on the mean of the second and third readings with an automated device. Socioeconomic status was estimated with indicators of education, occupation and wealth. RESULTS: In all 9254 people were examined. Age-adjusted prevalence (%) among men/ women aged 35-64 years was 27.1/30.2 for BP > or = 140/90 mmHg or antihypertensive medication, 13.1/17.7 for BP > or = 160/95 mmHg or antihypertensive medication, 28.0/27.4 for BMI of 25.0-29.9 kg/m(2), 6.9/17.4 for BMI > or = 30 kg/m(2), and 22.0/2.6 for smoking (> or = 1 cigarette per day). Prevalence of categories of drinking frequency and history of diabetes are also reported. After adjustment for covariates, SES was associated inversely with BP and smoking and directly with BMI. Body mass index was associated positively with BP (1.01 and 0.91 mmHg systolic BP per 1 kg/m(2) BMI in men and women, respectively) and inversely with smoking (-1.14 kg/m(2) in male smokers versus non-smokers). Hypertension treatment rates were low, particularly in people of low SES. CONCLUSIONS: High prevalence of several cardiovascular risk factors in the urban population of a low-income country stresses the need for early public health interventions and adaptation of the health care infrastructure to meet the emerging challenge of cardiovascular disease. The direct SES-BMI association may drive increasing BMI and BP while the population becomes more affluent.