Displaying publications 121 - 140 of 2018 in total

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  1. Minhat HS, Mohd Amin R
    J Community Health, 2012 Aug;37(4):840-7.
    PMID: 22160659 DOI: 10.1007/s10900-011-9518-8
    Leisure participation has been proven to be beneficial and has a positive link to successful ageing. This study aims to explore the sociodemographic determinants of leisure participation among the Malaysian elderly. A cross-sectional study was conducted among persons aged 60 years and above, purposively selected from eight health clinics in the state of Selangor. Leisure participation was measured using a validated Leisure Participation Questionnaire specific for Malaysian elderly, consisting of 25 activities, categorized into 4 categories, namely recreational (physical), cognitive, social and productive. Frequency of such participation was measured on a 6-point scale. Its association with sociodemographic variables was examined using inferential and regression analysis. 268 participants were involved in this study (response rate = 100%). The most common daily leisure activities were having conversations while relaxing (78.7%), watching television (74.6%) and reading (63.4%). The least frequently done leisure activities were from the recreational and cognitive categories. The activities were weakly correlated to each other, reflecting the lack of diversity of leisure activities among respondents. Education was the main predictor for leisure participation among elderly, with higher educational level is associated with high RAS (B = 1.020, P < 0.05), CAS (B = 1.580, P < 0.05) and SAS (B = 1.276, P < 0.05). Education level, marital status and locality were important determinants of leisure participation among elderly, with education being the main predictor. Further studies exploring the effective method of educating the ageing society are recommended.
    Matched MeSH terms: Rural Population/statistics & numerical data*; Urban Population/statistics & numerical data*
  2. Khairiyah AM, Razak IA, Raja-Latifah RJ, Tan BS, Norain AT, Noor-Aliyah I, et al.
    Asia Pac J Public Health, 2009 Apr;21(2):184-95.
    PMID: 19190002 DOI: 10.1177/1010539509331788
    The objective of this study is to share cost analysis methodology and to obtain cost estimates for posterior restorations in public sector dental clinics. Two urban and 2 rural dental clinics in Selangor state were selected. Only cases of 1 posterior restoration per visit by dental officers were included over 6 months. One capsulated amalgam type, 1 capsulated tooth-colored, and 1 non-capsulated tooth-colored material were selected. A clinical pathway form was formulated to collect data per patient. Annual capital and recurrent expenditures were collected per clinic. The mean cost of an amalgam restoration was RM 30.96 (sdRM 7.86); and tooth-colored restorations ranged from RM 33.00 (sdRM 8.43) to RM 41.10 (sdRM 10.61). Wherein 1 USD = RM 2.8. Restoration costs were 35% to 55% higher in clinics in rural areas than in urban areas. The findings demonstrate economy of scale for clinic operation and restoration costs with higher patient load. Costs per restoration were higher in rural than in urban dental clinics. More studies are recommended to address the dearth of dental costs data in Malaysia.
    Matched MeSH terms: Rural Population/statistics & numerical data; Urban Population/statistics & numerical data
  3. Hakim SL, Gan CC, Malkit K, Azian MN, Chong CK, Shaari N, et al.
    PMID: 17877212
    In April 2004, an outbreak of acute diarrheal illness occurred among the Orang Asli (aborigine) in the Cameron Highlands, Pahang State, Peninsular Malaysia, where rotavirus was later implicated as the cause. In the course of the epidemic investigation, stool samples were collected and examined for infectious agents including parasites. Soil transmitted helminthes (STH), namely Ascaris lumbricoides (25.7%), Trichuris trichiura (31.1%) and hookworm (8.1%), and intestinal protozoa, which included Giardia lamblia (17.6%), Entamoeba histolytica/E. dispar (9.4%), Blastocystis hominis (8.1%) and Cryptosporidium parvum (2.7%), were detected. Forty-four (59.5%) were infected with at least one parasite, 24 (32.4%), 12 (16.2%) and 8 (10.8%) had single, double and triple parasitic infections, respectively. STH were prevalent with infections occurring as early as in infancy. Giardia lamblia, though the most commonly found parasite in samples from symptomatic subjects, was within the normally reported rate of giardiasis among the various communities in Malaysia, and was an unlikely cause of the outbreak. However, heavy pre-existing parasitic infections could have contributed to the severity of the rotavirus diarrheal outbreak.
    Matched MeSH terms: Population Surveillance/methods; Population Groups*
  4. Sein KK
    Midwifery, 2013 Nov;29(11):1257-63.
    PMID: 23415368 DOI: 10.1016/j.midw.2012.11.012
    to examine the postpartum beliefs and practices among young women (15-24 years)
    Matched MeSH terms: Rural Population/statistics & numerical data; Urban Population/statistics & numerical data
  5. Kok KY, Rajendran P
    PLoS One, 2016;11(3):e0150558.
    PMID: 26943630 DOI: 10.1371/journal.pone.0150558
    The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
    Matched MeSH terms: Population Density
  6. PMID: 12349388
    Matched MeSH terms: Population; Population Characteristics; Population Dynamics*
  7. Fold N, Wangel A
    Third World Plann Rev, 1998 May;20(2):165-77.
    PMID: 12295215
    Matched MeSH terms: Population; Population Characteristics; Urban Population*
  8. Schmidt JD
    Third World Plann Rev, 1998 May;20(2):127-45.
    PMID: 12295213
    Matched MeSH terms: Population; Population Characteristics; Urban Population*
  9. CIRDAP Dev Dig, 1998 Dec.
    PMID: 12322095
    Matched MeSH terms: Population; Population Characteristics; Population Growth*
  10. Reprowatch, 1999 May;19(3-4):4.
    PMID: 12322208
    Matched MeSH terms: Population; Population Dynamics; Population Growth*
  11. Biddlecom AE, Domingo LJ
    J Cross Cult Gerontol, 1996 Mar;11(1):109-14.
    PMID: 12292274
    Matched MeSH terms: Population; Population Characteristics; Population Dynamics*
  12. Ying SL
    J Southeast Asian Stud, 1992 Mar;23(1):112-32.
    PMID: 12286188
    Matched MeSH terms: Population; Population Characteristics; Population Dynamics*
  13. Noor Hassim I, Rampal KG
    Med J Malaysia, 1994 Mar;49(1):78-85.
    PMID: 8057996
    A cross sectional study to determine the prevalence of hearing loss and hearing impairment was conducted on 286 male subjects from a rural area. The sample was chosen by using a simple random sampling method. Prevalence of symptoms of tinnitus, ear disease, ear drum perforation and infection of external auditory meatus was 19.0 per cent, 6.7 per cent, 3.5 per cent and 0.4 per cent respectively. Air conduction audiometry tests showed the prevalences of hearing impairment of the left, right and both ears (aged 15-30 years) were 5.9%, 8.8% and 0% respectively. The prevalence of hearing loss increased with age. The higher frequencies (> 4KHz) appeared to be more affected than the lower frequencies.
    Matched MeSH terms: Population Surveillance*; Rural Population*
  14. Agus MR
    Warasan Prachakon Lae Sangkhom, 1990 Jan;2(2):205-21, 242-3.
    PMID: 12283536
    The focus of this study is on urbanization in Malaysia. "This paper is divided into three parts. The first part examines the trend of uneven urban development in West Malaysia. The second part discusses the change [in] ethnic composition of urban population between 1970 and 1980 intercensal period. The third part analyses the impact of the urbanization process on the Malays in the context of housing problems of the lower income groups." (SUMMARY IN THA)
    Matched MeSH terms: Population; Population Characteristics; Urban Population*
  15. Chang MS, Jute N
    Med J Malaysia, 1982 Sep;37(3):205-10.
    PMID: 7176997
    A total of 73 localities covering 4,894 premises and 26, 712 breeding habitats were surveyed in 1980 to determine and establish the density and distribution pattern of Aedes aegypti and Aedes albopictus in Sarawak. A similar pattern has been observed in the density of the Aedes aegypti and Aedes albopictus. The number of houses positive with Aedes larvae were found to be highest in the coastal areas followed by the inland rural areas. The Aedes aegypti Breteau Index (B.I.) of 0-525 in the coastal areas is the highest followed by 0-207.5 in the inland rural areas. The study undertaken has now revealed that both the Aedes aegypti and Aedes albopictus are widespread in the State.
    Matched MeSH terms: Population Density
  16. Yeoh PH
    Med J Malaysia, 1988 Sep;43(3):195-9.
    PMID: 3241576
    Matched MeSH terms: Population
  17. Concepcion M
    Rev Bras Estud Popul, 1987 Jan-Jul;4(1):61-76.
    PMID: 12280935
    Matched MeSH terms: Population; Population Dynamics; Population Growth*
  18. Osteria TS
    PMID: 12269204
    "This paper examines recent trends in urbanization in four selected ASEAN countries--Indonesia, Malaysia, the Philippines and Thailand--giving particular attention to the scale and pace of urbanization, the unique features of urban communities, and the health changes and adjustments that accompany urban development in these countries."
    Matched MeSH terms: Population; Population Characteristics; Urban Population*
  19. Meyer DR
    Stud Comp Int Dev, 1986;21(1):3-22.
    PMID: 12314582
    Matched MeSH terms: Population*; Urban Population*
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